Encoder, decoder, encoding method, and decoding method

ABSTRACT

Provided is an encoder that achieves further improvement. The encoder includes processing circuitry and memory. Using the memory, the processing circuitry: obtains two prediction images from two reference pictures; derives a luminance gradient value of each pixel position in each of the two prediction images; derives a luminance local motion estimation value of each pixel position in a current block; generates a luminance final prediction image using a luminance value and the luminance gradient value in each of the two prediction images, and the luminance local motion estimation value of the current block; and generates a chrominance final prediction image using at least one of the luminance gradient value of each of the two prediction images or the luminance local motion estimation value of the current block, and chrominance of each of the two prediction images.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. continuation application of PCT InternationalPatent Application Number PCT/JP2018/020875 filed on May 31, 2018,claiming the benefit of priority of U.S. Provisional Patent ApplicationNo. 62/514264 filed on Jun. 2, 2017, the entire contents of which arehereby incorporated by reference.

BACKGROUND 1. Technical Field

The present disclosure relates to an encoder, a decoder, an encodingmethod, and a decoding method.

2. Description of the Related Art

A video coding standard called High-Efficiency Video Coding (HEVC) hasbeen standardized by Joint Collaborative Team on Video Coding (JCT-VC)(see H.265 (ISO/IEC 23008-2 HEVC (High Efficiency Video Coding)), forexample).

SUMMARY

An encoder according to one aspect of the present disclosure includesprocessing circuitry and memory. Using the memory, the processingcircuitry: generates a luminance final prediction image and achrominance final prediction image by performing inter frame predictionon a current block; and encodes the current block using the luminancefinal prediction image and the chrominance final prediction image. Theinter frame prediction includes: obtaining two prediction images fromtwo reference pictures by performing motion compensation using twomotion vectors of the current block; deriving a luminance gradient valueof each pixel position in each of the two prediction images by referringto a pixel surrounding the pixel position in each of the two referencepictures; deriving a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block; generating the luminance finalprediction image using the luminance value and the luminance gradientvalue of the pixel position in each of the two prediction images, andthe luminance local motion estimation value of the pixel position in thecurrent block; and generating the chrominance final prediction imageusing at least one of the luminance gradient value of the pixel positionin each of the two prediction images or the luminance local motionestimation value of the pixel position in the current block, andchrominance of the pixel position in each of the two prediction images.

A decoder according to one aspect of the present disclosure includesprocessing circuitry and memory. Using the memory, the processingcircuitry: generates a luminance final prediction image and achrominance final prediction image by performing inter frame predictionon a current block; and decodes the current block using the luminancefinal prediction image and the chrominance final prediction image. Theinter frame prediction includes: obtaining two prediction images fromtwo reference pictures by performing motion compensation using twomotion vectors of the current block; deriving a luminance gradient valueof each pixel position in each of the two prediction images by referringto a pixel surrounding the pixel position in each of the two referencepictures; deriving a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block; generating the luminance finalprediction image using the luminance value and the luminance gradientvalue of the pixel position in each of the two prediction images, andthe luminance local motion estimation value of the pixel position in thecurrent block; and generating the chrominance final prediction imageusing at least one of the luminance gradient value of the pixel positionin each of the two prediction images or the luminance local motionestimation value of the pixel position in the current block, andchrominance of the pixel position in each of the two prediction images.

It should be noted that these general or specific aspects may beimplemented by a system, a method, an integrated circuit, a computerprogram, or a non-transitory computer-readable recording medium such asa compact disc read only memory (CD-ROM), or by any combination ofsystems, methods, integrated circuits, computer programs, or recordingmedia.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a block diagram illustrating a functional configuration of anencoder according to Embodiment 1.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1.

FIG. 3 is a chart indicating transform basis functions for eachtransform type.

FIG. 4A illustrates one example of a filter shape used in ALF.

FIG. 4B illustrates another example of a filter shape used in ALF.

FIG. 4C illustrates another example of a filter shape used in ALF.

FIG. 5A illustrates 67 intra prediction modes used in intra prediction.

FIG. 5B is a flow chart for illustrating an outline of a predictionimage correction process performed via OBMC processing.

FIG. 5C is a conceptual diagram for illustrating an outline of aprediction image correction process performed via OBMC processing.

FIG. 5D illustrates one example of FRUC.

FIG. 6 is for illustrating pattern matching (bilateral matching) betweentwo blocks along a motion trajectory.

FIG. 7 is for illustrating pattern matching (template matching) betweena template in the current picture and a block in a reference picture.

FIG. 8 is for illustrating a model assuming uniform linear motion.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks.

FIG. 9B is for illustrating an outline of a process for deriving amotion vector via merge mode.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

FIG. 10 is a block diagram illustrating a functional configuration of adecoder according to Embodiment 1.

FIG. 11 is a conceptual diagram illustrating generation of a finalprediction image in a BIO mode performed by an inter predictor inEmbodiment 2.

FIG. 12 is a flow chart illustrating an example of operations in the BIOmode performed by the inter predictor in Embodiment 2.

FIG. 13 is a flow chart illustrating another example of operations inthe BIO mode performed by the inter predictor in Embodiment 2.

FIG. 14 is a flow chart illustrating another example of operations inthe BIO mode performed by the inter predictor in Embodiment 2.

FIG. 15A is a block diagram illustrating an implementation example of anencoder in Embodiment 2.

FIG. 15B is a flow chart illustrating operations performed by theencoder including processing circuitry and memory in Embodiment 2.

FIG. 15C is a block diagram illustrating an implementation example of adecoder in Embodiment 2.

FIG. 15D is a flow chart illustrating operations performed by thedecoder including processing circuitry and memory in Embodiment 2.

FIG. 16 illustrates an overall configuration of a content providingsystem for implementing a content distribution service.

FIG. 17 illustrates one example of an encoding structure in scalableencoding.

FIG. 18 illustrates one example of an encoding structure in scalableencoding.

FIG. 19 illustrates an example of a display screen of a web page.

FIG. 20 illustrates an example of a display screen of a web page.

FIG. 21 illustrates an example of a smartphone.

FIG. 22 is a block diagram illustrating a configuration example of asmartphone.

DETAILED DESCRIPTION OF THE EMBODIMENTS

An encoder according to one aspect of the present disclosure includesprocessing circuitry and memory. Using the memory, the processingcircuitry: generates a luminance final prediction image and achrominance final prediction image by performing inter frame predictionon a current block; and encodes the current block using the luminancefinal prediction image and the chrominance final prediction image. Theinter frame prediction includes: obtaining two prediction images fromtwo reference pictures by performing motion compensation using twomotion vectors of the current block; deriving a luminance gradient valueof each pixel position in each of the two prediction images by referringto a pixel surrounding the pixel position in each of the two referencepictures; deriving a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block; generating the luminance finalprediction image using the luminance value and the luminance gradientvalue of the pixel position in each of the two prediction images, andthe luminance local motion estimation value of the pixel position in thecurrent block; and generating the chrominance final prediction imageusing at least one of the luminance gradient value of the pixel positionin each of the two prediction images or the luminance local motionestimation value of the pixel position in the current block, andchrominance of the pixel position in each of the two prediction images.It should be noted that a local motion estimation value is also referredto as a correction motion vector.

With this, the chrominance final prediction image is generated using atleast one of the luminance gradient value of each pixel position in eachof the two prediction images or the luminance local motion estimationvalue of each pixel position in the current block. In other words,instead of the chrominance gradient value, the luminance gradient valueof each pixel position in each of the two prediction images is used ingenerating the chrominance final prediction image. Alternatively,instead of the chrominance local motion estimation value, the luminancelocal motion estimation value of each pixel position in the currentblock is used in generating the chrominance final prediction image.Alternatively, instead of the chrominance gradient value and thechrominance local motion estimation value, the luminance gradient valueof each pixel position in each of the two prediction images and theluminance local motion estimation value of each pixel position in thecurrent block are used in generating the chrominance final predictionimage.

Accordingly, the derivation of at least one of the chrominance gradientvalue of each pixel position in each of the two prediction images or thechrominance local motion estimation value of each pixel position in thecurrent block based on the chrominance can be omitted from thegeneration of the chrominance final prediction image. As a result, thereis a possibility of reducing the processing load of the encoder andsimplifying the configuration of the encoder. In other words, althoughgenerating not only the luminance final prediction image but also thechrominance final prediction image using a bi-directional optical flow(BIO) mode increases the processing load, it is possible to suppress anincrease in processing load. Further, because the chrominance finalprediction image is generated using at least one of the luminancegradient value or the luminance local motion estimation value withoutgenerating the chrominance final prediction image directly from theluminance final prediction image, it is possible to suppress a decreasein prediction accuracy for the chrominance final prediction image.

Moreover, the inter frame prediction may further include deriving achrominance local motion estimation value for each pixel position in thecurrent block using the chrominance and the luminance gradient value ineach of the two prediction images, the chrominance and the luminancegradient value corresponding to the pixel position in the current block,and in the generating of the chrominance final prediction image, thechrominance final prediction image may be generated using the luminancegradient value of each pixel position in each of the two predictionimages, the chrominance local motion estimation value of the pixelposition in the current block, and the chrominance of the pixel positionin each of the two prediction images.

With this, instead of the chrominance gradient value, the luminancegradient value of each pixel position in each of the two predictionimages is used in generating the chrominance final prediction image.Accordingly, the derivation of the chrominance gradient value of eachpixel position in each of the two prediction images based on thechrominance can be omitted from the generation of the chrominance finalprediction image. As a result, there is a possibility of reducing theprocessing load of the encoder and simplifying the configuration of theencoder.

Moreover, the inter frame prediction may further include deriving achrominance gradient value of each pixel position in each of the twoprediction images by referring to a pixel surrounding each pixelposition in each of the two reference pictures, and in the generating ofthe chrominance final prediction image, the chrominance final predictionimage may be generated using the chrominance gradient value of the pixelposition in each of the two prediction images, the luminance localmotion estimation value of each pixel position in the current block, andthe chrominance of the pixel position in each of the two predictionimages.

With this, instead of the chrominance local motion estimation value, theluminance local motion estimation value of each pixel position in thecurrent block is used in generating the chrominance final predictionimage. Accordingly, the calculation of the chrominance local motionestimation value of each pixel position in the current block based onthe chrominance can be omitted from the generation of the chrominancefinal prediction image. As a result, there is a possibility of reducingthe processing load of the encoder and simplifying the configuration ofthe encoder.

Moreover, in the generating of the chrominance final prediction image, achrominance gradient value may be calculated using C=α×L+β, where Ldenotes a luminance gradient value, C denotes a chrominance gradientvalue, and α and β each denote a real number, and the chrominance finalprediction image may be generated based on the chrominance gradientvalue calculated using the luminance gradient value. Alternatively, inthe generating of the chrominance final prediction image, a chrominancelocal motion estimation value may be calculated using C=α×L+β, where Ldenotes a luminance local motion estimation value, C denotes achrominance local motion estimation value, and α and β each denote areal number, and the chrominance final prediction image may be generatedbased on the chrominance local motion estimation value calculated usingthe luminance local motion estimation value.

With this, the chrominance gradient value and the chrominance localmotion estimation value can be appropriately calculated from theluminance gradient value and the luminance local motion estimationvalue, respectively. As a result, there is a possibility of reducing theprediction errors of the chrominance final prediction image, and apossibility of improving the coding efficiency.

A decoder according to one aspect of the present disclosure includesprocessing circuitry and memory. Using the memory, the processingcircuitry: generates a luminance final prediction image and achrominance final prediction image by performing inter frame predictionon a current block; and decodes the current block using the luminancefinal prediction image and the chrominance final prediction image. Theinter frame prediction includes: obtaining two prediction images fromtwo reference pictures by performing motion compensation using twomotion vectors of the current block; deriving a luminance gradient valueof each pixel position in each of the two prediction images by referringto a pixel surrounding the pixel position in each of the two referencepictures; deriving a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block; generating the luminance finalprediction image using the luminance value and the luminance gradientvalue of the pixel position in each of the two prediction images, andthe luminance local motion estimation value of the pixel position in thecurrent block; and generating the chrominance final prediction imageusing at least one of the luminance gradient value of the pixel positionin each of the two prediction images or the luminance local motionestimation value of the pixel position in the current block, andchrominance of the pixel position in each of the two prediction images.

With this, the chrominance final prediction image is generated using atleast one of the luminance gradient value of each pixel position in eachof the two prediction images or the luminance local motion estimationvalue of each pixel position in the current block. In other words,instead of the chrominance gradient value, the luminance gradient valueof each pixel position in each of the two prediction images is used ingenerating the chrominance final prediction image. Alternatively,instead of the chrominance local motion estimation value, the luminancelocal motion estimation value of each pixel position in the currentblock is used in generating the chrominance final prediction image.Alternatively, instead of the chrominance gradient value and thechrominance local motion estimation value, the luminance gradient valueof each pixel position in each of the two prediction images and theluminance local motion estimation value of each pixel position in thecurrent block are used in generating the chrominance final predictionimage.

Accordingly, the derivation of at least one of the chrominance gradientvalue of each pixel position in each of the two prediction images or thechrominance local motion estimation value of each pixel position in thecurrent block based on the chrominance can be omitted from thegeneration of the chrominance final prediction image. As a result, thereis a possibility of reducing the processing load of the decoder andsimplifying the configuration of the decoder. In other words, althoughgenerating not only the luminance final prediction image but also thechrominance final prediction image using a bi-directional optical flow(BIO) mode increases the processing load, it is possible to suppress anincrease in processing load. Further, because the chrominance finalprediction image is generated using at least one of the luminancegradient value or the luminance local motion estimation value withoutgenerating the chrominance final prediction image directly from theluminance final prediction image, it is possible to suppress a decreasein prediction accuracy for the chrominance final prediction image.

Moreover, the inter frame prediction may further include deriving achrominance local motion estimation value for each pixel position in thecurrent block using the chrominance and the luminance gradient value ineach of the two prediction images, the chrominance and the luminancegradient value corresponding to the pixel position in the current block,and in the generating of the chrominance final prediction image, thechrominance final prediction image may be generated using the luminancegradient value of each pixel position in each of the two predictionimages, the chrominance local motion estimation value of the pixelposition in the current block, and the chrominance of the pixel positionin each of the two prediction images.

With this, instead of the chrominance gradient value, the luminancegradient value of each pixel position in each of the two predictionimages is used in generating the chrominance final prediction image.Accordingly, the derivation of the chrominance gradient value of eachpixel position in each of the two prediction images based on thechrominance can be omitted from the generation of the chrominance finalprediction image. As a result, there is a possibility of reducing theprocessing load of the decoder and simplifying the configuration of thedecoder.

Moreover, the inter frame prediction may further include deriving achrominance gradient value of each pixel position in each of the twoprediction images by referring to a pixel surrounding each pixelposition in each of the two reference pictures, and in the generating ofthe chrominance final prediction image, the chrominance final predictionimage may be generated using the chrominance gradient value of the pixelposition in each of the two prediction images, the luminance localmotion estimation value of each pixel position in the current block, andthe chrominance of the pixel position in each of the two predictionimages.

With this, instead of the chrominance local motion estimation value, theluminance local motion estimation value of each pixel position in thecurrent block is used in generating the chrominance final predictionimage. Accordingly, the calculation of the chrominance local motionestimation value of each pixel position in the current block based onthe chrominance can be omitted from the generation of the chrominancefinal prediction image. As a result, there is a possibility of reducingthe processing load of the decoder and simplifying the configuration ofthe decoder. Moreover, in the generating of the chrominance finalprediction image, a chrominance gradient value may be calculated usingC=α×L+β, where L denotes a luminance gradient value, C denotes achrominance gradient value, and α and β each denote a real number, andthe chrominance final prediction image may be generated based on thechrominance gradient value calculated using the luminance gradientvalue. Alternatively, in the generating of the chrominance finalprediction image, a chrominance local motion estimation value may becalculated using C=α×L+β, where L denotes a luminance local motionestimation value, C denotes a chrominance local motion estimation value,and α and β each denote a real number, and the chrominance finalprediction image may be generated based on the chrominance local motionestimation value calculated using the luminance local motion estimationvalue.

With this, the chrominance gradient value and the chrominance localmotion estimation value can be appropriately calculated from theluminance gradient value and the luminance local motion estimationvalue, respectively. As a result, there is a possibility of reducing theprediction errors of the chrominance final prediction image, and apossibility of improving the coding efficiency.

Hereinafter, embodiments will be described with reference to thedrawings.

Note that the embodiments described below each show a general orspecific example. The numerical values, shapes, materials, components,the arrangement and connection of the components, steps, order of thesteps, etc., indicated in the following embodiments are mere examples,and therefore are not intended to limit the scope of the claims.Furthermore, among the components in the following embodiments,components not recited in any one of the independent claims defining themost generic concept of the present disclosure are described as optionalcomponents.

Embodiment 1

First, an outline of Embodiment 1 will be presented. Embodiment 1 is oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in subsequent description of aspects of thepresent disclosure are applicable. Note that Embodiment 1 is merely oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in the description of aspects of the presentdisclosure are applicable. The processes and/or configurations presentedin the description of aspects of the present disclosure can also beimplemented in an encoder and a decoder different from those accordingto Embodiment 1.

When the processes and/or configurations presented in the description ofaspects of the present disclosure are applied to Embodiment 1, forexample, any of the following may be performed.

(1) regarding the encoder or the decoder according to Embodiment 1,among components included in the encoder or the decoder according to

Embodiment 1, substituting a component corresponding to a componentpresented in the description of aspects of the present disclosure with acomponent presented in the description of aspects of the presentdisclosure;

(2) regarding the encoder or the decoder according to Embodiment 1,implementing discretionary changes to functions or implemented processesperformed by one or more components included in the encoder or thedecoder according to Embodiment 1, such as addition, substitution, orremoval, etc., of such functions or implemented processes, thensubstituting a component corresponding to a component presented in thedescription of aspects of the present disclosure with a componentpresented in the description of aspects of the present disclosure;

(3) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, implementing discretionary changes such asaddition of processes and/or substitution, removal of one or more of theprocesses included in the method, and then substituting a processescorresponding to a process presented in the description of aspects ofthe present disclosure with a process presented in the description ofaspects of the present disclosure;

(4) combining one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(5) combining a component including one or more functions included inone or more components included in the encoder or the decoder accordingto

Embodiment 1, or a component that implements one or more processesimplemented by one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(6) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, among processes included in the method,substituting a process corresponding to a process presented in thedescription of aspects of the present disclosure with a processpresented in the description of aspects of the present disclosure; and(7) combining one or more processes included in the method implementedby the encoder or the decoder according to Embodiment 1 with a processpresented in the description of aspects of the present disclosure.

Note that the implementation of the processes and/or configurationspresented in the description of aspects of the present disclosure is notlimited to the above examples. For example, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be implemented in a device used for a purpose differentfrom the moving picture/picture encoder or the moving picture/picturedecoder disclosed in

Embodiment 1. Moreover, the processes and/or configurations presented inthe description of aspects of the present disclosure may beindependently implemented. Moreover, processes and/or configurationsdescribed in different aspects may be combined.

[Encoder Outline]

First, the encoder according to Embodiment 1 will be outlined. FIG. 1 isa block diagram illustrating a functional configuration of encoder 100according to Embodiment 1. Encoder 100 is a moving picture/pictureencoder that encodes a moving picture/picture block by block.

As illustrated in FIG. 1, encoder 100 is a device that encodes a pictureblock by block, and includes splitter 102, subtractor 104, transformer106, quantizer 108, entropy encoder 110, inverse quantizer 112, inversetransformer 114, adder 116, block memory 118, loop filter 120, framememory 122, intra predictor 124, inter predictor 126, and predictioncontroller 128.

Encoder 100 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.Alternatively, encoder 100 may be realized as one or more dedicatedelectronic circuits corresponding to splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, loop filter 120, intrapredictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, each component included in encoder 100 will be described.

[Splitter]

Splitter 102 splits each picture included in an input moving pictureinto blocks, and outputs each block to subtractor 104. For example,splitter 102 first splits a picture into blocks of a fixed size (forexample, 128×128). The fixed size block is also referred to as codingtree unit (CTU). Splitter 102 then splits each fixed size block intoblocks of variable sizes (for example, 64×64 or smaller), based onrecursive quadtree and/or binary tree block splitting. The variable sizeblock is also referred to as a coding unit (CU), a prediction unit (PU),or a transform unit (TU). Note that in this embodiment, there is no needto differentiate between CU, PU, and TU; all or some of the blocks in apicture may be processed per CU, PU, or TU.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1. In FIG. 2, the solid lines represent block boundaries ofblocks split by quadtree block splitting, and the dashed lines representblock boundaries of blocks split by binary tree block splitting.

Here, block 10 is a square 128×128 pixel block (128×128 block). This128×128 block 10 is first split into four square 64×64 blocks (quadtreeblock splitting).

The top left 64×64 block is further vertically split into two rectangle32×64 blocks, and the left 32×64 block is further vertically split intotwo rectangle 16×64 blocks (binary tree block splitting). As a result,the top left 64×64 block is split into two 16×64 blocks 11 and 12 andone 32×64 block 13.

The top right 64×64 block is horizontally split into two rectangle 64×32blocks 14 and 15 (binary tree block splitting).

The bottom left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The top left block and the bottom rightblock among the four 32×32 blocks are further split. The top left 32×32block is vertically split into two rectangle 16×32 blocks, and the right16×32 block is further horizontally split into two 16×16 blocks (binarytree block splitting). The bottom right 32×32 block is horizontallysplit into two 32×16 blocks (binary tree block splitting). As a result,the bottom left 64×64 block is split into 16×32 block 16, two 16×16blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16 blocks 21and 22.

The bottom right 64×64 block 23 is not split.

As described above, in FIG. 2, block 10 is split into 13 variable sizeblocks 11 through 23 based on recursive quadtree and binary tree blocksplitting. This type of splitting is also referred to as quadtree plusbinary tree (QTBT) splitting.

Note that in FIG. 2, one block is split into four or two blocks(quadtree or binary tree block splitting), but splitting is not limitedto this example. For example, one block may be split into three blocks(ternary block splitting). Splitting including such ternary blocksplitting is also referred to as multi-type tree (MBT) splitting.

[Subtractor]

Subtractor 104 subtracts a prediction signal (prediction sample) from anoriginal signal (original sample) per block split by splitter 102. Inother words, subtractor 104 calculates prediction errors (also referredto as residuals) of a block to be encoded (hereinafter referred to as acurrent block). Subtractor 104 then outputs the calculated predictionerrors to transformer 106.

The original signal is a signal input into encoder 100, and is a signalrepresenting an image for each picture included in a moving picture (forexample, a luma signal and two chroma signals). Hereinafter, a signalrepresenting an image is also referred to as a sample.

[Transformer]

Transformer 106 transforms spatial domain prediction errors intofrequency domain transform coefficients, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a predefined discrete cosine transform (DCT) ordiscrete sine transform (DST) to spatial domain prediction errors.

Note that transformer 106 may adaptively select a transform type fromamong a plurality of transform types, and transform prediction errorsinto transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 3 is a chart indicating transform basisfunctions for each transform type. In FIG. 3, N indicates the number ofinput pixels. For example, selection of a transform type from among theplurality of transform types may depend on the prediction type (intraprediction and inter prediction), and may depend on intra predictionmode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an AMT flag) and information indicating the selectedtransform type is signalled at the CU level. Note that the signaling ofsuch information need not be performed at the CU level, and may beperformed at another level (for example, at the sequence level, picturelevel, slice level, tile level, or CTU level).

Moreover, transformer 106 may apply a secondary transform to thetransform coefficients (transform result). Such a secondary transform isalso referred to as adaptive secondary transform (AST) or non-separablesecondary transform (NSST). For example, transformer 106 applies asecondary transform to each sub-block (for example, each 4×4 sub-block)included in the block of the transform coefficients corresponding to theintra prediction errors. Information indicating whether to apply NSSTand information related to the transform matrix used in NSST aresignalled at the CU level. Note that the signaling of such informationneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, or CTU level). Here, a separable transform is a method inwhich a transform is performed a plurality of times by separatelyperforming a transform for each direction according to the number ofdimensions input. A non-separable transform is a method of performing acollective transform in which two or more dimensions in amultidimensional input are collectively regarded as a single dimension.

In one example of a non-separable transform, when the input is a 4×4block, the 4×4 block is regarded as a single array including 16components, and the transform applies a 16×16 transform matrix to thearray.

Moreover, similar to above, after an input 4×4 block is regarded as asingle array including 16 components, a transform that performs aplurality of Givens rotations on the array (i.e., a Hypercube-GivensTransform) is also one example of a non-separable transform.

[Quantizer]

Quantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in apredetermined scanning order, the transform coefficients of the currentblock, and quantizes the scanned transform coefficients based onquantization parameters (QP) corresponding to the transformcoefficients. Quantizer 108 then outputs the quantized transformcoefficients (hereinafter referred to as quantized coefficients) of thecurrent block to entropy encoder 110 and inverse quantizer 112.

A predetermined order is an order for quantizing/inverse quantizingtransform coefficients. For example, a predetermined scanning order isdefined as ascending order of frequency (from low to high frequency) ordescending order of frequency (from high to low frequency).

A quantization parameter is a parameter defining a quantization stepsize (quantization width). For example, if the value of the quantizationparameter increases, the quantization step size also increases. In otherwords, if the value of the quantization parameter increases, thequantization error increases.

[Entropy Encoder]

Entropy encoder 110 generates an encoded signal (encoded bitstream) byvariable length encoding quantized coefficients, which are inputs fromquantizer 108. More specifically, entropy encoder 110, for example,binarizes quantized coefficients and arithmetic encodes the binarysignal.

[Inverse Quantizer]

Inverse quantizer 112 inverse quantizes quantized coefficients, whichare inputs from quantizer 108. More specifically, inverse quantizer 112inverse quantizes, in a predetermined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114.

[Inverse Transformer]

Inverse transformer 114 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 112. More specifically, inverse transformer 114 restores theprediction errors of the current block by applying an inverse transformcorresponding to the transform applied by transformer 106 on thetransform coefficients. Inverse transformer 114 then outputs therestored prediction errors to adder 116. Note that since information islost in quantization, the restored prediction errors do not match theprediction errors calculated by subtractor 104. In other words, therestored prediction errors include quantization errors.

[Adder]

Adder 116 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 114, and prediction samples,which are inputs from prediction controller 128. Adder 116 then outputsthe reconstructed block to block memory 118 and loop filter 120. Areconstructed block is also referred to as a local decoded block. [BlockMemory]

Block memory 118 is storage for storing blocks in a picture to beencoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 118 storesreconstructed blocks output from adder 116.

[Loop Filter]

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF), a sample adaptiveoffset (SAO), and an adaptive loop filter (ALF).

In ALF, a least square error filter for removing compression artifactsis applied. For example, one filter from among a plurality of filters isselected for each 2×2 sub-block in the current block based on directionand activity of local gradients, and is applied.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, 15 or 25 classes). The classification of the sub-block is basedon gradient directionality and activity. For example, classificationindex C is derived based on gradient directionality D (for example, 0 to2 or 0 to 4) and gradient activity A (for example, 0 to 4) (for example,C=5D+A). Then, based on classification index C, each sub-block iscategorized into one out of a plurality of classes (for example, 15 or25 classes).

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by summing gradients of a plurality ofdirections and quantizing the sum.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in ALF is, for example, a circular symmetricfilter shape. FIG. 4A through FIG. 4C illustrate examples of filtershapes used in ALF. FIG. 4A illustrates a 5×5 diamond shape filter, FIG.4B illustrates a 7×7 diamond shape filter, and FIG. 4C illustrates a 9×9diamond shape filter. Information indicating the filter shape issignalled at the picture level. Note that the signaling of informationindicating the filter shape need not be performed at the picture level,and may be performed at another level (for example, at the sequencelevel, slice level, tile level, CTU level, or CU level).

The enabling or disabling of ALF is determined at the picture level orCU level. For example, for luma, the decision to apply ALF or not isdone at the CU level, and for chroma, the decision to apply ALF or notis done at the picture level. Information indicating whether ALF isenabled or disabled is signalled at the picture level or CU level. Notethat the signaling of information indicating whether ALF is enabled ordisabled need not be performed at the picture level or CU level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, or CTU level).

The coefficients set for the plurality of selectable filters (forexample, 15 or 25 filters) is signalled at the picture level. Note thatthe signaling of the coefficients set need not be performed at thepicture level, and may be performed at another level (for example, atthe sequence level, slice level, tile level, CTU level, CU level, orsub-block level).

[Frame Memory]

Frame memory 122 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 122 stores reconstructed blocks filtered byloop filter 120.

[Intra Predictor]

Intra predictor 124 generates a prediction signal (intra predictionsignal) by intra predicting the current block with reference to a blockor blocks in the current picture and stored in block memory 118 (alsoreferred to as intra frame prediction). More specifically, intrapredictor 124 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of predefined intra prediction modes. Theintra prediction modes include one or more non-directional predictionmodes and a plurality of directional prediction modes.

The one or more non-directional prediction modes include, for example,planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard (see NPL 1). Theplurality of directional prediction modes include, for example, the 33directional prediction modes defined in the H.265/HEVC standard. Notethat the plurality of directional prediction modes may further include32 directional prediction modes in addition to the 33 directionalprediction modes (for a total of 65 directional prediction modes). FIG.5A illustrates 67 intra prediction modes used in intra prediction (twonon-directional prediction modes and 65 directional prediction modes).The solid arrows represent the 33 directions defined in the H.265/HEVCstandard, and the dashed arrows represent the additional 32 directions.

Note that a luma block may be referenced in chroma block intraprediction. In other words, a chroma component of the current block maybe predicted based on a luma component of the current block. Such intraprediction is also referred to as cross-component linear model (CCLM)prediction. Such a chroma block intra prediction mode that references aluma block (referred to as, for example, CCLM mode) may be added as oneof the chroma block intra prediction modes.

Intra predictor 124 may correct post-intra-prediction pixel values basedon horizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC or not (referred to as, for example, a PDPC flag)is, for example, signalled at the CU level. Note that the signaling ofthis information need not be performed at the CU level, and may beperformed at another level (for example, on the sequence level, picturelevel, slice level, tile level, or CTU level).

[Inter Predictor]

Inter predictor 126 generates a prediction signal (inter predictionsignal) by inter predicting the current block with reference to a blockor blocks in a reference picture, which is different from the currentpicture and is stored in frame memory 122 (also referred to as interframe prediction). Inter prediction is performed per current block orper sub-block (for example, per 4×4 block) in the current block. Forexample, inter predictor 126 performs motion estimation in a referencepicture for the current block or sub-block. Inter predictor 126 thengenerates an inter prediction signal of the current block or sub-blockby motion compensation by using motion information (for example, amotion vector) obtained from motion estimation. Inter predictor 126 thenoutputs the generated inter prediction signal to prediction controller128.

The motion information used in motion compensation is signalled. Amotion vector predictor may be used for the signaling of the motionvector. In other words, the difference between the motion vector and themotion vector predictor may be signalled.

Note that the inter prediction signal may be generated using motioninformation for a neighboring block in addition to motion informationfor the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated per sub-blockin the current block by calculating a weighted sum of a predictionsignal based on motion information obtained from motion estimation and aprediction signal based on motion information for a neighboring block.Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In such an OBMC mode, information indicating sub-block size for OBMC(referred to as, for example, OBMC block size) is signalled at thesequence level. Moreover, information indicating whether to apply theOBMC mode or not (referred to as, for example, an OBMC flag) issignalled at the CU level. Note that the signaling of such informationneed not be performed at the sequence level and CU level, and may beperformed at another level (for example, at the picture level, slicelevel, tile level, CTU level, or sub-block level).

Hereinafter, the OBMC mode will be described in further detail. FIG. 5Bis a flowchart and FIG. 5C is a conceptual diagram for illustrating anoutline of a prediction image correction process performed via OBMCprocessing.

First, a prediction image (Pred) is obtained through typical motioncompensation using a motion vector (MV) assigned to the current block.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV_L) of the encoded neighboring left block to the currentblock, and a first pass of the correction of the prediction image ismade by superimposing the prediction image and Pred_L.

Similarly, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) of the encoded neighboring upper block to the currentblock, and a second pass of the correction of the prediction image ismade by superimposing the prediction image resulting from the first passand Pred_U. The result of the second pass is the final prediction image.

Note that the above example is of a two-pass correction method using theneighboring left and upper blocks, but the method may be a three-pass orhigher correction method that also uses the neighboring right and/orlower block.

Note that the region subject to superimposition may be the entire pixelregion of the block, and, alternatively, may be a partial block boundaryregion.

Note that here, the prediction image correction process is described asbeing based on a single reference picture, but the same applies when aprediction image is corrected based on a plurality of referencepictures. In such a case, after corrected prediction images resultingfrom performing correction based on each of the reference pictures areobtained, the obtained corrected prediction images are furthersuperimposed to obtain the final prediction image.

Note that the unit of the current block may be a prediction block and,alternatively, may be a sub-block obtained by further dividing theprediction block.

One example of a method for determining whether to implement OBMCprocessing is by using an obmc_flag, which is a signal that indicateswhether to implement OBMC processing. As one specific example, theencoder determines whether the current block belongs to a regionincluding complicated motion. The encoder sets the obmc_flag to a valueof “1” when the block belongs to a region including complicated motionand implements OBMC processing when encoding, and sets the obmc_flag toa value of “0” when the block does not belong to a region includingcomplication motion and encodes without implementing OBMC processing.The decoder switches between implementing OBMC processing or not bydecoding the obmc_flag written in the stream and performing the decodingin accordance with the flag value.

Note that the motion information may be derived on the decoder sidewithout being signalled. For example, a merge mode defined in theH.265/HEVC standard may be used. Moreover, for example, the motioninformation may be derived by performing motion estimation on thedecoder side. In this case, motion estimation is performed without usingthe pixel values of the current block.

Here, a mode for performing motion estimation on the decoder side willbe described. A mode for performing motion estimation on the decoderside is also referred to as pattern matched motion vector derivation(PMMVD) mode or frame rate up-conversion (FRUC) mode.

One example of FRUC processing is illustrated in FIG. 5D. First, acandidate list (a candidate list may be a merge list) of candidates eachincluding a motion vector predictor is generated with reference tomotion vectors of encoded blocks that spatially or temporally neighborthe current block. Next, the best candidate MV is selected from among aplurality of candidate MVs registered in the candidate list. Forexample, evaluation values for the candidates included in the candidatelist are calculated and one candidate is selected based on thecalculated evaluation values.

Next, a motion vector for the current block is derived from the motionvector of the selected candidate. More specifically, for example, themotion vector for the current block is calculated as the motion vectorof the selected candidate (best candidate MV), as-is. Alternatively, themotion vector for the current block may be derived by pattern matchingperformed in the vicinity of a position in a reference picturecorresponding to the motion vector of the selected candidate. In otherwords, when the vicinity of the best candidate MV is searched via thesame method and an MV having a better evaluation value is found, thebest candidate MV may be updated to the MV having the better evaluationvalue, and the MV having the better evaluation value may be used as thefinal MV for the current block. Note that a configuration in which thisprocessing is not implemented is also acceptable.

The same processes may be performed in cases in which the processing isperformed in units of sub-blocks.

Note that an evaluation value is calculated by calculating thedifference in the reconstructed image by pattern matching performedbetween a region in a reference picture corresponding to a motion vectorand a predetermined region. Note that the evaluation value may becalculated by using some other information in addition to thedifference.

The pattern matching used is either first pattern matching or secondpattern matching. First pattern matching and second pattern matching arealso referred to as bilateral matching and template matching,respectively.

In the first pattern matching, pattern matching is performed between twoblocks along the motion trajectory of the current block in two differentreference pictures. Therefore, in the first pattern matching, a regionin another reference picture conforming to the motion trajectory of thecurrent block is used as the predetermined region for theabove-described calculation of the candidate evaluation value.

FIG. 6 is for illustrating one example of pattern matching (bilateralmatching) between two blocks along a motion trajectory. As illustratedin FIG. 6, in the first pattern matching, two motion vectors (MV0, MV1)are derived by finding the best match between two blocks along themotion trajectory of the current block (Cur block) in two differentreference pictures (Ref0, Ref1). More specifically, a difference between(i) a reconstructed image in a specified position in a first encodedreference picture (Ref0) specified by a candidate MV and (ii) areconstructed picture in a specified position in a second encodedreference picture (Ref1) specified by a symmetrical MV scaled at adisplay time interval of the candidate MV may be derived, and theevaluation value for the current block may be calculated by using thederived difference. The candidate MV having the best evaluation valueamong the plurality of candidate MVs may be selected as the final MV.

Under the assumption of continuous motion trajectory, the motion vectors(MV0, MV1) pointing to the two reference blocks shall be proportional tothe temporal distances (TD0, TD1) between the current picture (Cur Pic)and the two reference pictures (Ref0, Ref1). For example, when thecurrent picture is temporally between the two reference pictures and thetemporal distance from the current picture to the two reference picturesis the same, the first pattern matching derives a mirror basedbi-directional motion vector.

In the second pattern matching, pattern matching is performed between atemplate in the current picture (blocks neighboring the current block inthe current picture (for example, the top and/or left neighboringblocks)) and a block in a reference picture. Therefore, in the secondpattern matching, a block neighboring the current block in the currentpicture is used as the predetermined region for the above-describedcalculation of the candidate evaluation value.

FIG. 7 is for illustrating one example of pattern matching (templatematching) between a template in the current picture and a block in areference picture. As illustrated in FIG. 7, in the second patternmatching, a motion vector of the current block is derived by searching areference picture (Ref0) to find the block that best matches neighboringblocks of the current block (Cur block) in the current picture (CurPic). More specifically, a difference between (i) a reconstructed imageof an encoded region that is both or one of the neighboring left andneighboring upper region and (ii) a reconstructed picture in the sameposition in an encoded reference picture (Ref0) specified by a candidateMV may be derived, and the evaluation value for the current block may becalculated by using the derived difference. The candidate MV having thebest evaluation value among the plurality of candidate MVs may beselected as the best candidate MV.

Information indicating whether to apply the FRUC mode or not (referredto as, for example, a FRUC flag) is signalled at the CU level. Moreover,when the FRUC mode is applied (for example, when the FRUC flag is set totrue), information indicating the pattern matching method (first patternmatching or second pattern matching) is signalled at the CU level. Notethat the signaling of such information need not be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

Here, a mode for deriving a motion vector based on a model assuminguniform linear motion will be described. This mode is also referred toas a bi-directional optical flow (BIO) mode.

FIG. 8 is for illustrating a model assuming uniform linear motion. InFIG. 8, (v_(x), v_(y)) denotes a velocity vector, and τ₀ and τ₁ denotetemporal distances between the current picture (Cur Pic) and tworeference pictures (Ref₀, (MVx₀, MVy₀) denotes a motion vectorcorresponding to reference picture Ref0, and (MVx₁, MVy₁) denotes amotion vector corresponding to reference picture Ref₁.

Here, under the assumption of uniform linear motion exhibited byvelocity vector (v_(x), v_(y)), (MVx₀, MVy₀) and (MVx₁, MVy₁) arerepresented as (v_(x)τ₀, v_(y)τ₀) and (−v_(x)τ₁, −v_(y)τ₁),respectively, and the following optical flow equation is given.

MATH. 1

∂I ^((k)) /∂t+v _(x) ∂I ^((k)) /∂x+v _(y) ∂I ^((k)) /∂y=0   (¹)

Here, I^((k)) denotes a luma value from reference picture k (k=0, 1)after motion compensation. This optical flow equation shows that the sumof (i) the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference picture, and (iii) the product of the vertical velocityand the vertical component of the spatial gradient of a referencepicture is equal to zero. A motion vector of each block obtained from,for example, a merge list is corrected pixel by pixel based on acombination of the optical flow equation and Hermite interpolation. Notethat a motion vector may be derived on the decoder side using a methodother than deriving a motion vector based on a model assuming uniformlinear motion. For example, a motion vector may be derived for eachsub-block based on motion vectors of neighboring blocks.

Here, a mode in which a motion vector is derived for each sub-blockbased on motion vectors of neighboring blocks will be described. Thismode is also referred to as affine motion compensation prediction mode.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks. In FIG. 9A, the currentblock includes 16 4×4 sub-blocks. Here, motion vector v₀ of the top leftcorner control point in the current block is derived based on motionvectors of neighboring sub-blocks, and motion vector v₁ of the top rightcorner control point in the current block is derived based on motionvectors of neighboring blocks. Then, using the two motion vectors v₀ andv₁, the motion vector (v_(x), V_(y)) of each sub-block in the currentblock is derived using Equation 2 below.

$\begin{matrix}{{MATH}.\mspace{14mu} 2} & \; \\\left\{ \begin{matrix}{\nu_{x} = {{\frac{\left( {v_{1x} - v_{0x}} \right)}{w}x} - {\frac{\left( {v_{1y} - v_{0y}} \right)}{w}y} + v_{0x}}} \\{v_{y} = {{\frac{\left( {v_{1y} - v_{0y}} \right)}{w}x} + {\frac{\left( {v_{1x} - v_{0x}} \right)}{w}y} + \nu_{0y}}}\end{matrix} \right. & (2)\end{matrix}$

Here, x and y are the horizontal and vertical positions of thesub-block, respectively, and w is a predetermined weighted coefficient.

Such an affine motion compensation prediction mode may include a numberof modes of different methods of deriving the motion vectors of the topleft and top right corner control points. Information indicating such anaffine motion compensation prediction mode (referred to as, for example,an affine flag) is signalled at the CU level. Note that the signaling ofinformation indicating the affine motion compensation prediction modeneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, CTU level, or sub-block level).

[Prediction Controller]

Prediction controller 128 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto subtractor 104 and adder 116.

Here, an example of deriving a motion vector via merge mode in a currentpicture will be given. FIG. 9B is for illustrating an outline of aprocess for deriving a motion vector via merge mode.

First, an MV predictor list in which candidate MV predictors areregistered is generated. Examples of candidate MV predictors include:spatially neighboring MV predictors, which are MVs of encoded blockspositioned in the spatial vicinity of the current block; a temporallyneighboring MV predictor, which is an MV of a block in an encodedreference picture that neighbors a block in the same location as thecurrent block; a combined MV predictor, which is an MV generated bycombining the MV values of the spatially neighboring MV predictor andthe temporally neighboring MV predictor; and a zero MV predictor, whichis an MV whose value is zero.

Next, the MV of the current block is determined by selecting one MVpredictor from among the plurality of MV predictors registered in the MVpredictor list.

Furthermore, in the variable-length encoder, a merge_idx, which is asignal indicating which MV predictor is selected, is written and encodedinto the stream.

Note that the MV predictors registered in the MV predictor listillustrated in FIG. 9B constitute one example. The number of MVpredictors registered in the MV predictor list may be different from thenumber illustrated in FIG. 9B, the MV predictors registered in the MVpredictor list may omit one or more of the types of MV predictors givenin the example in FIG. 9B, and the MV predictors registered in the MVpredictor list may include one or more types of MV predictors inaddition to and different from the types given in the example in FIG.9B.

Note that the final MV may be determined by performing DMVR processing(to be described later) by using the MV of the current block derived viamerge mode.

Here, an example of determining an MV by using DMVR processing will begiven.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

First, the most appropriate MVP set for the current block is consideredto be the candidate MV, reference pixels are obtained from a firstreference picture, which is a picture processed in the L0 direction inaccordance with the candidate MV, and a second reference picture, whichis a picture processed in the L1 direction in accordance with thecandidate MV, and a template is generated by calculating the average ofthe reference pixels.

Next, using the template, the surrounding regions of the candidate MVsof the first and second reference pictures are searched, and the MV withthe lowest cost is determined to be the final MV. Note that the costvalue is calculated using, for example, the difference between eachpixel value in the template and each pixel value in the regionssearched, as well as the MV value.

Note that the outlines of the processes described here are fundamentallythe same in both the encoder and the decoder.

Note that processing other than the processing exactly as describedabove may be used, so long as the processing is capable of deriving thefinal MV by searching the surroundings of the candidate MV.

Here, an example of a mode that generates a prediction image by usingLIC processing will be given.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

First, an MV is extracted for obtaining, from an encoded referencepicture, a reference image corresponding to the current block.

Next, information indicating how the luminance value changed between thereference picture and the current picture is extracted and a luminancecorrection parameter is calculated by using the luminance pixel valuesfor the encoded left neighboring reference region and the encoded upperneighboring reference region, and the luminance pixel value in the samelocation in the reference picture specified by the MV.

The prediction image for the current block is generated by performing aluminance correction process by using the luminance correction parameteron the reference image in the reference picture specified by the MV.

Note that the shape of the surrounding reference region illustrated inFIG. 9D is just one example; the surrounding reference region may have adifferent shape.

Moreover, although a prediction image is generated from a singlereference picture in this example, in cases in which a prediction imageis generated from a plurality of reference pictures as well, theprediction image is generated after performing a luminance correctionprocess, via the same method, on the reference images obtained from thereference pictures.

One example of a method for determining whether to implement LICprocessing is by using an lic_flag, which is a signal that indicateswhether to implement LIC processing. As one specific example, theencoder determines whether the current block belongs to a region ofluminance change. The encoder sets the lic_flag to a value of “1” whenthe block belongs to a region of luminance change and implements LICprocessing when encoding, and sets the lic_flag to a value of “0” whenthe block does not belong to a region of luminance change and encodeswithout implementing LIC processing. The decoder switches betweenimplementing LIC processing or not by decoding the lic_flag written inthe stream and performing the decoding in accordance with the flagvalue.

One example of a different method of determining whether to implementLIC processing is determining so in accordance with whether LICprocessing was determined to be implemented for a surrounding block. Inone specific example, when merge mode is used on the current block,whether LIC processing was applied in the encoding of the surroundingencoded block selected upon deriving the MV in the merge mode processingmay be determined, and whether to implement LIC processing or not can beswitched based on the result of the determination. Note that in thisexample, the same applies to the processing performed on the decoderside.

[Decoder Outline]

Next, a decoder capable of decoding an encoded signal (encodedbitstream) output from encoder 100 will be described. FIG. 10 is a blockdiagram illustrating a functional configuration of decoder 200 accordingto Embodiment 1. Decoder 200 is a moving picture/picture decoder thatdecodes a moving picture/picture block by block.

As illustrated in FIG. 10, decoder 200 includes entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, block memory210, loop filter 212, frame memory 214, intra predictor 216, interpredictor 218, and prediction controller 220.

Decoder 200 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, loop filter212, intra predictor 216, inter predictor 218, and prediction controller220. Alternatively, decoder 200 may be realized as one or more dedicatedelectronic circuits corresponding to entropy decoder 202, inversequantizer 204, inverse transformer 206, adder 208, loop filter 212,intra predictor 216, inter predictor 218, and prediction controller 220.

Hereinafter, each component included in decoder 200 will be described.

[Entropy Decoder]

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204.

[Inverse Quantizer]

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block), whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedcoefficients (i.e., transform coefficients) of the current block toinverse transformer 206.

[Inverse Transformer]

Inverse transformer 206 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesapplication of EMT or AMT (for example, when the AMT flag is set totrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type.

Moreover, for example, when information parsed from an encoded bitstreamindicates application of NSST, inverse transformer 206 applies asecondary inverse transform to the transform coefficients.

[Adder]

Adder 208 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 206, and prediction samples,which is an input from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

[Block Memory]

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 210 storesreconstructed blocks output from adder 208.

[Loop Filter]

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214and, for example, a display device.

When information indicating the enabling or disabling of ALF parsed froman encoded bitstream indicates enabled, one filter from among aplurality of filters is selected based on direction and activity oflocal gradients, and the selected filter is applied to the reconstructedblock. [Frame Memory]

Frame memory 214 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 214 stores reconstructed blocks filtered byloop filter 212.

[Intra Predictor]

Intra predictor 216 generates a prediction signal (intra predictionsignal) by intra prediction with reference to a block or blocks in thecurrent picture and stored in block memory 210. More specifically, intrapredictor 216 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 220.

Note that when an intra prediction mode in which a chroma block is intrapredicted from a luma block is selected, intra predictor 216 may predictthe chroma component of the current block based on the luma component ofthe current block.

Moreover, when information indicating the application of PDPC is parsedfrom an encoded bitstream, intra predictor 216 correctspost-intra-prediction pixel values based on horizontal/verticalreference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block with reference to areference picture stored in frame memory 214. Inter prediction isperformed per current block or per sub-block (for example, per 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or sub-block by motioncompensation by using motion information (for example, a motion vector)parsed from an encoded bitstream, and outputs the inter predictionsignal to prediction controller 220.

Note that when the information parsed from the encoded bitstreamindicates application of OBMC mode, inter predictor 218 generates theinter prediction signal using motion information for a neighboring blockin addition to motion information for the current block obtained frommotion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates application of FRUC mode, inter predictor 218 derives motioninformation by performing motion estimation in accordance with thepattern matching method (bilateral matching or template matching) parsedfrom the encoded bitstream. Inter predictor 218 then performs motioncompensation using the derived motion information.

Moreover, when BIO mode is to be applied, inter predictor 218 derives amotion vector based on a model assuming uniform linear motion. Moreover,when the information parsed from the encoded bitstream indicates thataffine motion compensation prediction mode is to be applied, interpredictor 218 derives a motion vector of each sub-block based on motionvectors of neighboring blocks.

[Prediction Controller]

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208.

EMBODIMENT 2

The encoder and the decoder in the above-described embodiment generate aluminance prediction image using the BIO mode. An encoder and a decoderin the present embodiment generate not only a luminance prediction imagebut also a chrominance prediction image using the BIO mode. Here,generating the chrominance prediction image using the BIO mode in thesame manner as the luminance prediction image increases a processingload. In view of this, the encoder and the decoder in the presentembodiment use a luminance parameter used in generating a luminanceprediction image using the BIO mode, in generating a chrominanceprediction image. With this, it is possible to simplify theconfiguration of each of the encoder and the decoder and reduce theprocessing load while improving prediction accuracy for a chrominanceprediction image.

It should be noted that the above-described luminance prediction imageand chrominance prediction image are different from a prediction imageobtained by performing motion compensation using two motion vectors of acurrent block to be encoded or decoded (i.e., a prediction block), andtwo reference pictures. In other words, the above-described luminanceprediction image and chrominance prediction image each are an image thatis generated using a prediction image obtained by performing motioncompensation, and is added to or subtracted from a current block toencode or decode the current block. Hereinafter, the above-describedluminance prediction image and chrominance prediction image are referredto as a luminance final prediction image and a chrominance finalprediction image, respectively, in distinction from a prediction imageobtained by performing motion compensation.

As with Embodiment 1, encoder 100 and decoder 200 in the presentembodiment have the configurations illustrated in FIG. 1 and FIG. 10,respectively. Unlike Embodiment 1, however, inter predictor 126 ofencoder 100 in the present embodiment uses a luminance parameter used ingenerating a luminance final prediction image using the BIO mode, ingenerating a chrominance final prediction image. Similarly, unlikeEmbodiment 1, inter predictor 218 of decoder 200 in the presentembodiment uses a luminance parameter used in generating a luminancefinal prediction image using the BIO mode, in generating a chrominancefinal prediction image. It should be noted that inter predictor 218 ofdecoder 200 generates a final prediction image in the BIO mode in thesame manner as inter predictor 126 of encoder 100. For this reason, adetailed description of how inter predictor 218 of decoder 200 generatesa final prediction image in the BIO mode is omitted, and the followingdescribes in detail how inter predictor 126 of encoder 100 generates afinal prediction image in the BIO mode.

[Generation of Final Prediction Image in BIO Mode]

FIG. 11 is a conceptual diagram illustrating generation of a finalprediction image in a BIO mode performed by inter predictor 126.

Inter predictor 126 derives two motion vectors of a current block: an L0motion vector (MV_L0) and an L1 motion vector (MV_L1). It should benoted that the current block is a block to be encoded for which a finalprediction image is generated by prediction, and is a prediction block,for example.

The L0 motion vector (MV_L0) is a motion vector for referring to an L0reference picture that is a processed picture, and the L1 motion vector(MV_L1) is a motion vector for referring to an L1 reference picture thatis a processed picture. The L0 reference picture and the L1 referencepicture are two reference pictures simultaneously referred to inperforming bi-prediction of the current block. It should be noted thatthe above-described processed pictures are encoded pictures processed byencoder 100. Moreover, inter predictor 126 may derive the L0 motionvector (MV_L0) and the L1 motion vector (MV_L1) using a normal interframe prediction mode, a merge mode, a FRUC mode, etc. For example, inthe normal inter frame prediction mode, inter predictor 126 derives theL0 motion vector (MV_L0) and the L1 motion vector (MV_L1) by performingmotion detection or motion estimation using an image of the currentblock. Information of these motion vectors is encoded. Furthermore, inthe normal inter frame prediction mode, decoder 200 derives the motionvectors by decoding the encoded information of the motion vectors.

Next, inter predictor 126 obtains an L0 prediction image by referring tothe L0 reference picture and performing motion compensation of thecurrent block using the L0 motion vector (MV_L0). For example, interpredictor 126 applies a motion compensation filter to an image in an L0reference pixel range including a block in the L0 reference pictureindicated from the current block by the L0 motion vector (MV_L0), andthe surroundings of the block. As a result, the L0 prediction image isobtained.

Moreover, inter predictor 126 calculates an L0 gradient image indicatinga spatial gradient of luminance in each pixel of the L0 predictionimage. For example, inter predictor 126 calculates the L0 gradient imageby referring to the luminance of each pixel in the L0 reference pixelrange including the block in the L0 reference picture indicated from thecurrent block by the L0 motion vector (MV_L0), and the surroundings ofthe block.

Next, inter predictor 126 obtains an L1 prediction image by referring tothe L1 reference picture and performing motion compensation of thecurrent block using the L1 motion vector (MV_L1). For example, interpredictor 126 applies a motion compensation filter to an image in an L1reference pixel range including a block in the L1 reference pictureindicated from the current block by the L1 motion vector (MV_L1), andthe surroundings of the block. As a result, the L1 prediction image isobtained.

Moreover, inter predictor 126 calculates an L1 gradient image indicatinga spatial gradient of luminance in each pixel of the L1 predictionimage. For example, inter predictor 126 calculates the L1 gradient imageby referring to the luminance of each pixel in the L1 reference pixelrange including the block in the L1 reference picture indicated from thecurrent block by the L1 motion vector (MV_L1), and the surroundings ofthe block.

Next, inter predictor 126 calculates a local motion estimation value foreach pixel position in the current block. Specifically, at the time,inter predictor 126 uses a luminance value of each pixel position in theL0 prediction image, a luminance gradient value of each pixel positionin the L0 gradient image, a luminance value of each pixel position inthe L1 prediction image, and a luminance gradient value of each pixelposition in the L1 gradient image. Such a local motion estimation valueis a luminance local motion estimation value. In addition, the localmotion estimation value is also referred to as a correction motionvector (correction MV).

Then, inter predictor 126 derives a luminance correction value for eachpixel position in the current block using a luminance gradient value ofa current pixel position in the L0 gradient image, a luminance gradientvalue of a current pixel position in the L1 gradient image, and localmotion estimation values of the current pixel positions. After that,inter predictor 126 derives a final prediction luminance value for eachpixel position in the current block using the luminance value of thecurrent pixel position in the L0 prediction image, the luminance valueof the current pixel position in the L1 prediction image, and theluminance correction value. A luminance final prediction image to whichthe BIO mode is applied is derived by deriving such a final predictionluminance value for each pixel position in the current block.

In other words, the prediction luminance value, which is obtained usingthe luminance value of the current pixel position in the L0 predictionimage and the luminance value of the current pixel position in the L1prediction image, is corrected with the luminance correction value. Inother words, the prediction image, which is obtained using the L0prediction image and the L1 prediction image, is corrected using thespatial gradients of the luminance in the L0 prediction image and the L1prediction image.

It should be noted that specifically, the following equation (3) may beused in deriving a local motion estimation value and a luminancecorrection value.

$\begin{matrix}{{MATH}.\mspace{14mu} 3} & \; \\\left. \begin{matrix}{{G_{x}\left\lbrack {x,y} \right\rbrack} = {{{I_{x}}^{0}\left\lbrack {x,y} \right\rbrack} + {{I_{x}}^{1}\left\lbrack {x,y} \right\rbrack}}} \\{{G_{y}\left\lbrack {x,y} \right\rbrack} = {{{I_{y}}^{0}\left\lbrack {x,y} \right\rbrack} + {{I_{y}}^{1}\left\lbrack {x,y} \right\rbrack}}} \\{{\Delta\;{I\left\lbrack {x,y} \right\rbrack}} = {{I^{0}\left\lbrack {x,y} \right\rbrack} - {I^{1}\left\lbrack {x,y} \right\rbrack}}} \\{{G_{x}{G_{y}\left\lbrack {x,y} \right\rbrack}} = {{G_{x}\left\lbrack {x,y} \right\rbrack}^{*}{G_{y}\left\lbrack {x,y} \right\rbrack}}} \\{{{sG}_{x}{G_{y}\left\lbrack {x,y} \right\rbrack}} = {\Sigma_{\lbrack{i,{j\lbrack{\epsilon\Omega}}}}{w\left\lbrack {i,j} \right\rbrack}^{*}G_{x}{G_{y}\left\lbrack {i,j} \right\rbrack}}} \\{{{{sG}_{x}}^{2}\left\lbrack {x,y} \right\rbrack} = {\Sigma_{{\lbrack{i,j}\rbrack}{\epsilon\Omega}}{w\left\lbrack {i,j} \right\rbrack}^{*}{G_{x}\left\lbrack {i,j} \right\rbrack}^{*}{G_{x}\left\lbrack {i,j} \right\rbrack}}} \\{{{{sG}_{y}}^{2}\left\lbrack {x,y} \right\rbrack} = {\Sigma_{{\lbrack{i,j}\rbrack}{\epsilon\Omega}}{w\left\lbrack {i,j} \right\rbrack}^{*}{G_{y}\left\lbrack {i,j} \right\rbrack}^{*}{G_{y}\left\lbrack {i,j} \right\rbrack}}} \\{{{sG}_{x}{{dI}\left\lbrack {x,y} \right\rbrack}} = {\Sigma_{{\lbrack{i,j}\rbrack}{\epsilon\Omega}}{w\left\lbrack {i,j} \right\rbrack}^{*}{G_{x}\left\lbrack {i,j} \right\rbrack}^{*}\Delta\;{I\left\lbrack {i,j} \right\rbrack}}} \\{{{sG}_{y}{{dI}\left\lbrack {x,y} \right\rbrack}} = {\Sigma_{{\lbrack{i,j}\rbrack}{\epsilon\Omega}}{w\left\lbrack {i,j} \right\rbrack}^{*}{G_{y}\left\lbrack {i,j} \right\rbrack}^{*}\Delta\;{I\left\lbrack {i,j} \right\rbrack}}} \\{{u\left\lbrack {x,y} \right\rbrack} = {{sG}_{x}{{{dI}\left\lbrack {x,y} \right\rbrack}/{{{sG}_{x}}^{2}\left\lbrack {x,y} \right\rbrack}}}} \\{{v\left\lbrack {x,y} \right\rbrack} = {\left( {{{sG}_{y}{{dI}\left\lbrack {x,y} \right\rbrack}} - {{u\left\lbrack {x,y} \right\rbrack}^{*}{sG}_{x}{G_{y}\left\lbrack {x,y} \right\rbrack}}} \right)/{{{sG}_{y}}^{2}\left\lbrack {x,y} \right\rbrack}}} \\\begin{matrix}{{b\left\lbrack {x,y} \right\rbrack} = {{{u\left\lbrack {x,y} \right\rbrack}^{*}\left( {{{I_{x}}^{0}\left\lbrack {x,y} \right\rbrack} - {{I_{x}}^{1}\left\lbrack {x,y} \right\rbrack}} \right)} +}} \\{{v\left\lbrack {x,y} \right\rbrack}^{*}\left( {{{I_{y}}^{0}\left\lbrack {x,y} \right\rbrack} - {{I_{y}}^{1}\left\lbrack {x,y} \right\rbrack}} \right.}\end{matrix} \\{{p = \left( {{I^{0}\left\lbrack {x,y} \right\rbrack} + {I^{1}\left\lbrack {x,y} \right\rbrack} + {b\left\lbrack {x,y} \right\rbrack}} \right)}\operatorname{>>}1}\end{matrix} \right\} & (3)\end{matrix}$

In equation (3), I_(x) ⁽⁰⁾[x, y] denotes a horizontal luminance gradientvalue of a pixel position [x, y] in the L0 gradient image. I_(x) ⁽¹⁾[x,y] denotes a horizontal luminance gradient value of a pixel position [x,y] in the L1 gradient image. I_(y) ⁽⁰⁾[x, y] denotes a verticalluminance gradient value of the pixel position [x, y] in the L0 gradientimage. I_(y) ⁽¹⁾[x, y] denotes a vertical luminance gradient value ofthe pixel position [x, y] in the L1 gradient image.

Moreover, in equation (3), I⁰[x, y] denotes a luminance value of a pixelposition [x, y] in the L0 prediction image. I¹[x, y] denotes a luminancevalue of a pixel position [x, y] in the L1 prediction image. ΔI[x, y]denotes a different between the luminance value of the pixel position[x, y] in the L0 prediction image and the luminance value of the pixelposition [x, y] in the L1 prediction image.

Moreover, in equation (3), Ω denotes, for example, a set of pixelpositions included in a region having the pixel position [x, y] at thecenter. w[i, j] denotes a weight coefficient for a pixel position [i,j]. The same value may be used for w[i, j]. G_(x)[x, y] G_(y)[x, y],G_(x)G_(y)[x, y], sG_(x)G_(y)[x, y], sG_(x) ²[x, y], sG_(y) ²[x, y]sG_(x)dI[x, y], sG_(y)dI[x, y], etc. are supplemental calculated values.

Moreover, in equation (3), u[x, y] denotes a horizontal value includedin a luminance local motion estimation value of a pixel position [x, y].v[x, y] denotes a vertical value included in the luminance local motionestimation value of the pixel position [x, y]. b[x, y] denotes aluminance correction value of the pixel position [x, y]. p[x, y] denotesa final prediction luminance value of the pixel position [x, y].

As just described, in the inter frame prediction using the BIO mode,inter predictor 126 in the present embodiment first obtains the twoprediction images from the two reference pictures by performing motioncompensation using the two motion vectors of the current block. Next,inter predictor 126 derives the luminance gradient value of each pixelposition in each of the two prediction images by referring to the pixelsurrounding the pixel position in each of the two reference pictures.Then, inter predictor 126 derives the luminance local motion estimationvalue for each pixel position in the current block by using theluminance value and the luminance gradient value in each of the twoprediction images, the luminance value and the luminance gradient valuecorresponding to the pixel position. After that, inter predictor 126generates the luminance final prediction image using the luminance valueand the luminance gradient value of each pixel position in each of thetwo prediction images, and the luminance local motion estimation valueof each pixel position in the current block.

Here, generating not only the luminance final prediction image but alsothe chrominance final prediction image using the BIO mode increases theprocessing load. In view of this, inter predictor 126 in the presentembodiment uses the luminance parameter derived to generate theluminance final prediction image using the BIO mode, in generating thechrominance final prediction image using the BIO mode. In other words,the luminance parameter is used in generating the chrominance finalprediction image using the BIO mode. The luminance parameter is at leastone of the luminance gradient value of each pixel position in each ofthe two prediction images or the luminance local motion estimation valueof each pixel position in the current block. Accordingly, it is possibleto suppress an increase in processing load.

[Use of Luminance Gradient Value and Luminance Local Motion EstimationValue]

For example, inter predictor 126 uses both a luminance gradient valueand a luminance local motion estimation value in generating achrominance final prediction image using the BIO mode.

FIG. 12 is a flow chart illustrating an example of operations in the BIOmode performed by inter predictor 126.

First, inter predictor 126 performs steps S101 to S103 on an L0reference picture. For example, regarding the L0 reference picture,inter predictor 126 derives an L0 motion vector (MV) of a predictionblock that is a current block (step S101). Next, inter predictor 126obtains an L0 prediction image by performing motion compensation usingthe derived L0 motion vector and the L0 reference picture (step S102).Then, inter predictor 126 derives a luminance gradient value of eachpixel position in the L0 prediction image (step S103). An L0 luminancegradient image is generated from the luminance gradient value of eachpixel position.

As with the L0 reference picture, inter predictor 126 also performssteps S101 to S103 on an L1 reference picture. With this, interpredictor 126 obtains an L1 prediction image and further derives aluminance gradient value of each pixel position in the L1 predictionimage, that is, an L1 luminance gradient image.

Next, inter predictor 126 determines whether processing is to beperformed for luminance or chrominance (step S104). For example, wheninter predictor 126 performs step S104 for the first time, interpredictor 126 determines that the processing is to be performed forluminance, and when inter predictor 126 performs step S104 again, interpredictor 126 determines that the processing is to be performed forchrominance.

Here, when inter predictor 126 determines that the processing is to beperformed for luminance (LUMINANCE in step S104), inter predictor 126performs steps S105 and S106 on each of the pixel positions in theprediction block that is the current block.

In other words, inter predictor 126 derives luminance local motionestimation values t[x, y] and v[x, y] in a current pixel positionaccording to, for example, the above equation (3) (step S105). Next,inter predictor 126 generates a final prediction luminance value p[x, y]in the current pixel position (step S106). Luminance values I⁰[x, y] andI¹[x, y] in the current pixel position in each of the L0 predictionimage and the L1 prediction image, luminance gradient values I_(x) ⁰[x,y], I_(y) ⁰[x, y], I_(x) ¹[x, y], and I_(y) ¹[x, y], and the luminancelocal motion estimation values u[x, y] and v[x, y] in the current pixelposition are used in generating the final prediction luminance valuep[x, y].

By performing such steps S104 and S105 on each pixel position, interpredictor 126 generates a luminance final prediction image including thefinal prediction luminance value of the pixel position.

Then, inter predictor 126 determines whether a luminance finalprediction image and a chrominance final prediction image have beengenerated (step S109). Here, when inter predictor 126 determines thatthe luminance final prediction image and the chrominance finalprediction image have not been generated (No in step S109), interpredictor 126 repeats step S104 and the subsequent steps.

After that, when inter predictor 126 determines at the second round ofstep S104 that the processing is to be performed for chrominance(CHROMINANCE in step S104), inter predictor 126 performs the processingon each pixel position in the prediction block that is the currentblock. In other words, inter predictor 126 performs steps S107 and S108on each pixel position in the prediction block.

Specifically, inter predictor 126 generates a chrominance gradient valueand a chrominance local motion estimation value in the current pixelposition from the luminance gradient value and the luminance localmotion estimation value in the current pixel position (step S107).

For example, inter predictor 126 may calculate a chrominance gradientvalue and a chrominance local motion estimation value using C=α×L+β. Cand L denote a chrominance gradient value and a luminance gradientvalue, respectively. Alternatively, C and L denote a chrominance localmotion estimation value and a luminance local motion estimation value,respectively. α and β each denote a real number arbitrarily determined.For example, α and β are determined so that prediction accuracy becomeshigher. Moreover, inter predictor 126 may directly use a luminancegradient value and a luminance local motion estimation value as achrominance gradient value and a chrominance local motion estimationvalue. In this case, α and β are α=1 and β=0 in above C=α×L+β. Inaddition, in this case, there is a possibility of reducing an amount ofprocessing, compared to a case in which the prediction accuracy isincreased, that is, a case in which prediction errors are minimized.

Next, inter predictor 126 generates a final prediction chrominance p[x,y] in the current pixel position according to, for example, the aboveequation (3) (step S108). Chrominances I⁰[x, y] and I¹[x, y] in thecurrent pixel position in each of the L0 prediction image and the L1prediction image, chrominance gradient values I_(x) ⁰[x, y], I_(y) ⁰[x,y], I_(x) ¹[x, y], and I_(y) ¹[x, y] in the current pixel position ineach of the L0 gradient image and the L1 gradient image, and chrominancelocal motion estimation values u[x, y] and v[x, y] in the current pixelposition are used in generating the final prediction chrominance p[x,y]. It should be noted that the chrominance gradient values I_(x) ⁰[x,y], I_(y) ⁰[x, y], I_(x) ¹[x, y], and I_(y) ¹[x, y] and the chrominancelocal motion estimation values u[x, y] and v[x, y] may be generated fromluminance gradient values and luminance local motion estimation valuesas described above, and may be identical to the luminance gradientvalues and the luminance local motion estimation values.

By performing such steps S107 and S108 on each pixel position, interpredictor 126 generates a chrominance final prediction image includingthe final prediction chrominance p[x, y] of the pixel position.

As just described, in the example illustrated in FIG. 12, interpredictor 126 uses both the luminance gradient value and the luminancelocal motion estimation value in generating the chrominance finalprediction image using the BIO mode. In other words, in the exampleillustrated in FIG. 12, inter predictor 126 generates the chrominancefinal prediction image using the luminance gradient value of each pixelposition in each of the two prediction images, the luminance localmotion estimation value of each pixel position in the current block, andthe chrominance of each pixel position in each of the two predictionimages.

With this, instead of the chrominance gradient value and the chrominancelocal motion estimation value, the luminance gradient value of eachpixel position in each of the two prediction images and the luminancelocal motion estimation value of each pixel position in the currentblock are used in generating the chrominance final prediction image.Accordingly, the derivation of the chrominance gradient value of eachpixel position in each of the two prediction images and the chrominancelocal motion estimation value of each pixel position in the currentblock based on the chrominance can be omitted from the generation of thechrominance final prediction image. As a result, there is a possibilityof reducing the processing load of the encoder and simplifying theconfiguration of the encoder.

In other words, although generating not only the luminance finalprediction image but also the chrominance final prediction image usingthe BIO mode increases the processing load, it is possible to suppressthe increase in processing load. Further, because the chrominance finalprediction image is generated using the luminance gradient value and theluminance local motion estimation value without generating thechrominance final prediction image directly from the luminance finalprediction image, it is possible to suppress a decrease in predictionaccuracy for the chrominance final prediction image.

[Use of Luminance Gradient Value]

Inter predictor 126 may use, out of a luminance gradient value and aluminance local motion estimation value, only the luminance gradientvalue in generating a chrominance final prediction image using the BIOmode.

FIG. 1.3 is a flow chart illustrating an example of operations in theBIO mode performed by inter predictor 126.

First, similarly to the example illustrated in FIG. 12, inter predictor126 performs steps S101 to S103 on an L0 reference picture and an L1reference picture. In consequence, inter predictor 126 obtains an L0prediction image and an L1 prediction image. In addition, interpredictor 126 derives a luminance gradient value of each pixel positionin the L0 prediction image and a luminance gradient value of each pixelposition in the L1 prediction image, that is, an L0 gradient image andan L1 gradient image.

Next, inter predictor 126 determines whether processing is to beperformed for luminance or chrominance (step S104).

For example, when inter predictor 126 determines that the processing isto be performed for luminance (LUMINANCE in step S104), inter predictor126 performs steps S105 and S106 on each of the pixel positions in aprediction block that is a current block.

In other words, inter predictor 126 derives luminance local motionestimation values u[x, y] and v[x, y] in a current pixel positionaccording to, for example, the above equation (3) (step S105). Then,inter predictor 126 generates a final prediction luminance value p[x, y]in the current pixel position (step S106). By performing such steps S104and S105 on each pixel position, inter predictor 126 generates aluminance final prediction image including the final predictionluminance value of the pixel position.

After that, inter predictor 126 determines whether a luminance finalprediction image and a chrominance final prediction image have beengenerated (step S109). Here, when inter predictor 126 determines thatthe luminance final prediction image and the chrominance finalprediction image have not been generated (No in step S109), interpredictor 126 repeats step S104 and the subsequent steps.

Inter predictor 126 determines, for example, that the processing is tobe performed for chrominance (CHROMINANCE in step S104) so that theresult of the determination at the second round of step S104 isdifferent from the result of the determination at the first round ofstep S104. Here, inter predictor 126 performs the processing on eachpixel position in the prediction block that is the current block. Inother words, inter predictor 126 performs steps S111 to S113 on eachpixel position in the prediction block.

Specifically, inter predictor 126 generates, for each of the L0prediction image and the L1 prediction image, a chrominance gradientvalue of each pixel position in a range corresponding to a current pixelposition, from the luminance gradient value of each pixel position inthe range (step S111). For example, inter predictor 126 may calculate achrominance gradient value from the luminance gradient value usingC=α×L+β in the same manner as described above.

Next, inter predictor 126 derives chrominance local motion estimationvalues u[x, y] and v[x, y] in the current pixel position according to,for example, the above equation (3) (step S112). As shown by the aboveequation (3), chrominances I⁰[i, j] and I¹[i, j] of each pixel positionin a range of set Ω corresponding to the current pixel position and thechrominance gradient values I_(x) ⁰[i, j], I_(y) ⁰[i, j], I_(x) ¹[i, j],and I_(y) ¹[i, j] of the pixel position in the range of set Ω generatedin step S111 are used in generating the chrominance local motionestimation values u[x, y] and v[x, y] in the current pixel position.

Next, inter predictor 126 generates a final prediction chrominance p[x,y] in the current pixel position according to the above equation (3)(step S113).

The chrominances I_(x) ⁰[i, j], I_(y) ⁰[i, j], I_(x) ¹[i, j], and I_(y)¹[i, j] in the current pixel position in each of the L0 prediction imageand the L1 prediction image, the chrominance gradient values I_(x) ⁰[i,j], I_(y) ⁰[i, j], I_(x) ¹[i, j], and I_(y) ¹[i, j] in the current pixelposition generated in step S111, and the chrominance local motionestimation values u[x, y] and v[x, y] in the current pixel positiongenerated in step S112 are used in generating this final predictionchrominance p[x, y]. It should be noted that the chrominance gradientvalues I_(x) ⁰[i, j], I_(y) ⁰[i, j], I_(x) ¹[i, j], and I_(y) ¹[i, j]may be generated from luminance gradient values as described above, andmay be identical to the luminance gradient values.

By performing such steps S111 to S113 on each pixel position, interpredictor 126 generates a chrominance final prediction image includingthe final prediction chrominance p[x, y] of the pixel position.

As just described, in the example illustrated in FIG. 13, interpredictor 126 uses, out of the luminance gradient value and theluminance local motion estimation value, only the luminance gradientvalue in generating the chrominance final prediction image using the BIOmode.

In other words, in inter frame prediction, inter predictor 126 in thepresent embodiment derives, for each pixel position in the currentblock, the chrominance local motion estimation value using thechrominance in each of the two prediction images and corresponding tothe pixel position, and the luminance gradient value in each of the twoprediction images and corresponding to the pixel position. Then, ingenerating the chrominance final prediction image, inter predictor 126generates the chrominance final prediction image using the luminancegradient value of each pixel position in each of the two predictionimages, the chrominance local motion estimation value of each pixelposition in the current block, and the chrominance of each pixelposition in each of the two prediction images.

With this, instead of the chrominance gradient value, the luminancegradient value of each pixel position in each of the two predictionimages is used in generating the chrominance final prediction image.Accordingly, the derivation of the chrominance gradient value of eachpixel position in each of the two prediction images based on thechrominance can be omitted from the generation of the chrominance finalprediction image. As a result, there is a possibility of reducing theprocessing load of the encoder and simplifying the configuration of theencoder.

Moreover, in generating the chrominance final prediction image, interpredictor 126 in the present embodiment calculates the chrominancegradient value using C=α×L+β, where L denotes a luminance gradientvalue, C denotes a chrominance gradient value, and α and β denote realnumbers. After that, inter predictor 126 generates the chrominance finalprediction image based on the chrominance gradient value calculatedusing the luminance gradient value.

With this, it is possible to appropriately calculate the chrominancegradient value from the luminance gradient value. As a result, there isa possibility of reducing the prediction errors of the chrominance finalprediction image, and a possibility of improving the coding efficiency.

[Use of Luminance Local Motion Estimation Value]

Inter predictor 126 may use, out of a luminance gradient value and aluminance local motion estimation value, only the luminance local motionestimation value in generating a chrominance final prediction imageusing the BIO mode.

FIG. 14 is a flow chart illustrating an example of operations in the BIOmode performed by inter predictor 126.

First, similarly to the examples illustrated in FIG. 12 and FIG. 13,inter predictor 126 performs steps S101 to S103 on an L0 referencepicture and an L1 reference picture. In consequence, inter predictor 126obtains an L0 prediction image and an L1 prediction image. In addition,inter predictor 126 derives a luminance gradient value of each pixelposition in the L0 prediction image and a luminance gradient value ofeach pixel position in the L1 prediction image, that is, an L0 gradientimage and an L1 gradient image.

Next, inter predictor 126 determines whether processing is to beperformed for luminance or chrominance (step S104). For example, wheninter predictor 126 performs step S104 for the first time, interpredictor 126 determines that the processing is to be performed forluminance, and when inter predictor 126 performs step S104 again, interpredictor 126 determines that the processing is to be performed forchrominance.

Here, when inter predictor 126 determines that the processing is to beperformed for luminance (LUMINANCE in step S104), inter predictor 126performs steps S105 and S106 on each of the pixel positions in aprediction block that is a current block.

In other words, inter predictor 126 derives luminance local motionestimation values u[x, y] and v[x, y] in a current pixel positionaccording to, for example, the above equation (3) (step S105). Then,inter predictor 126 generates a final prediction luminance value p[x, y]in the current pixel position (step S106). By performing such steps S104and S105 on each pixel position, inter predictor 126 generates aluminance final prediction image including the final predictionluminance value of the pixel position.

Next, inter predictor 126 determines whether a luminance finalprediction image and a chrominance final prediction image have beengenerated (step S109). Here, when inter predictor 126 determines thatthe luminance final prediction image and the chrominance finalprediction image have not been generated (No in step S109), interpredictor 126 repeats step S104 and the subsequent steps.

Then, when inter predictor 126 determines at the second round of stepS104 that the processing is to be performed for chrominance (CHROMINANCEin step S104), inter predictor 126 performs the processing on each pixelposition in the prediction block that is the current block. In otherwords, inter predictor 126 performs steps S121 to S123 on each pixelposition in the prediction block.

Specifically, inter predictor 126 generates a chrominance local motionestimation value in the current pixel position from the luminance localmotion estimation value in the current pixel position (step S121). Forexample, inter predictor 126 may calculate a chrominance local motionestimation value from the luminance local motion estimation value usingC=α×L+β in the same manner as described above.

Next, inter predictor 126 derives a chrominance gradient valuecorresponding to the current pixel position in each of the L0 predictionimage and the L1 prediction image (step S122). Then, inter predictor 126generates a final prediction chrominance p[x, y] in the current pixelposition according to the above equation (3) (step S123). Thechrominances I⁰[x, y] and I¹[x, y] in the current pixel position in eachof the L0 prediction image and the L1 prediction image, the chrominancegradient values I_(x) ⁰[x, y], I_(y) ⁰[x, y], I_(x) ¹[x, y], and I_(y)¹[x, y] corresponding to the current pixel position generated in stepS122, and the chrominance local motion estimation values u[x, y] andv[x, y] in the current pixel position generated in step S121 are used ingenerating this final prediction chrominance p[x, y]. It should be notedthat the chrominance local motion estimation values u[x, y] and v[x, y]may be generated from luminance local motion estimation values asdescribed above, and may be identical to the luminance local motionestimation value.

By performing such steps S121 to S123 on each pixel position, interpredictor 126 generates a chrominance final prediction image includingthe final prediction chrominance p[x, y] of the pixel position.

As just described, in the example illustrated in FIG. 14, interpredictor 126 uses, out of the luminance gradient value and theluminance local motion estimation value, only the luminance local motionestimation value in generating the chrominance final prediction imageusing the BIO mode.

In other words, inter predictor 126 derives the chrominance gradientvalue of each pixel position in each of the two prediction images byreferring to a pixel surrounding the pixel position in each of the tworeference pictures. Then, in generating the chrominance final predictionimage, inter predictor 126 generates the chrominance final predictionimage using the chrominance gradient value of each pixel position ineach of the two prediction images, the luminance local motion estimationvalue of each pixel position in the current block, and the chrominanceof each pixel position in each of the two prediction images.

With this, instead of the chrominance local motion estimation value, theluminance local motion estimation value of each pixel position in thecurrent block is used in generating the chrominance final predictionimage. Accordingly, the calculation of the chrominance local motionestimation value of each pixel position in the current block based onthe chrominance can be omitted from the generation of the chrominancefinal prediction image. As a result, there is a possibility of reducingthe processing load of the encoder and simplifying the configuration ofthe encoder.

Moreover, in generating the chrominance final prediction image, interpredictor 126 in the present embodiment calculates the chrominance localmotion estimation value using C=α×L+β, where L denotes a luminance localmotion estimation value, C denotes a chrominance local motion estimationvalue, and α and β each denote a real number. Then, inter predictor 126generates the chrominance final prediction image based on thechrominance local motion estimation value calculated using the luminancelocal motion estimation value.

With this, it is possible to appropriately calculate the chrominancelocal motion estimation value from the luminance local motion estimationvalue. As a result, there is a possibility of reducing the predictionerrors of the chrominance final prediction image, and a possibility ofimproving the coding efficiency.

In encoder 100 in the present embodiment, as in the examples illustratedin FIG. 11 to FIG. 14, inter predictor 126 performs inter frameprediction using the BIO mode that uses the luminance parameter as thechrominance parameter. Moreover, inter predictor 218 of decoder 200 inthe present embodiment performs inter frame prediction using the BIOmode that uses the luminance parameter as the chrominance parameter, inthe same manner as inter predictor 126. It should be noted that wheninter predictor 218 of decoder 200 generates a luminance finalprediction image and a chrominance final prediction image using the BIOmode, a current block is a prediction block to be decoded.

With this, in the present embodiment, the chrominance final predictionimage is generated using at least one of the luminance gradient value ofeach pixel position in each of the two prediction images or theluminance local motion estimation value of each pixel position in thecurrent block. In other words, instead of the chrominance gradientvalue, the luminance gradient value of each pixel position in each ofthe two prediction images is used in generating the chrominance finalprediction image. Alternatively, instead of the chrominance local motionestimation value, the luminance local motion estimation value of eachpixel position in the current block is used in generating thechrominance final prediction image. Alternatively, instead of thechrominance gradient value and the chrominance local motion estimationvalue, the luminance gradient value of each pixel position in each ofthe two prediction images and the luminance local motion estimationvalue of each pixel position in the current block are used in generatingthe chrominance final prediction image.

Accordingly, the derivation of at least one of the chrominance gradientvalue of each pixel position in each of the two prediction images or thechrominance local motion estimation value of each pixel position in thecurrent block based on the chrominance can be omitted from thegeneration of the chrominance final prediction image. As a result, thereis a possibility of reducing the processing load of the encoder andsimplifying the configuration of the encoder. In other words, althoughgenerating not only the luminance final prediction image but also thechrominance final prediction image using the BIO mode increases theprocessing load, it is possible to suppress an increase in processingload. Further, because the chrominance final prediction image isgenerated using at least one of the luminance gradient value or theluminance local motion estimation value without generating thechrominance final prediction image directly from the luminance finalprediction image, it is possible to suppress a decrease in predictionaccuracy for the chrominance final prediction image.

[Variations]

Although inter predictor 126 derives a local motion estimation value foreach pixel in the aforementioned embodiment, inter predictor 126 mayderive a local motion estimation value for each sub-block that is animage data unit coarser than a pixel and finer than a current block.

For example, in the above-described equation (3), Ω may represent a setof pixel positions included in a sub-block. In addition, sGxGy[x, y],sGx2[x, y], sGy2[x, y], sGxdI[x, y], sGydI[x, y], u[x, y], and v[x, y]may be calculated not for each pixel but for each sub-block.

Moreover, encoder 100 and decoder 200 can apply a common BIO mode. Inother words, encoder 100 and decoder 200 can apply the BIO mode usingthe same method.

It should be noted that a chrominance resolution and a luminanceresolution may be different, as in the 4:2:0 format etc. In this case,inter predictor 126 may match the chrominance resolution and theluminance resolution, and may use a luminance parameter as a chrominanceparameter. A parameter is at least one of a gradient value or a localmotion estimation value. For example, inter predictor 126 may match thechrominance resolution and the luminance resolution by spatiallyaveraging parameters in respective pixel positions of luminancecorresponding to pixel positions of chrominance. Alternatively, interpredictor 126 may scale the luminance parameter, and use the scaledparameter as the chrominance parameter.

Furthermore, when inter predictor 126 generates a chrominance finalprediction image, inter predictor 126 may use only one or both of aluminance gradient value and a luminance local motion estimation value.In other words, inter predictor 12 may derive a chrominance local motionestimation value without using a luminance local motion estimationvalue, and may obtain a chrominance gradient value without using aluminance gradient value.

Furthermore, when chrominance includes Cr and Cb, inter predictor 126may derive a common parameter for Cr and Cb, and may independentlyderive different parameters for Cr and Cb. In addition, inter predictor126 may predict both a parameter for Cr and a parameter for Cb from aluminance parameter. Alternatively, inter predictor 126 may firstpredict the parameter for Cb from the luminance parameter, and then maypredict the parameter for Cr from the parameter for Cb. Conversely,inter predictor 126 may first predict the parameter for Cr from theluminance parameter, and then may predict the parameter for Cb from theparameter for Cr.

It should be noted that although inter frame prediction is performed onan image in YUV format, that is, a format in which an image includesluminance and chrominance in the present embodiment, inter frameprediction may be performed on an image in format other than such aformat. For example, an image format may be RGB format or HSV formatetc. In such a case, instead of generating a chrominance parameter froma luminance parameter, for example, inter predictor 126 may generate a Gparameter from an R parameter, and may generate an S parameter from an Hparameter.

[Implementation Examples]

FIG. 15A is a block diagram illustrating an implementation example of anencoder in Embodiment 2. Encoder la includes processing circuitry 2 aand memory 3 a. For example, the plurality of constituent elements ofencoder 100 illustrated in FIG. 1 are implemented by processingcircuitry 2 a and memory 3 a illustrated in FIG. 15A.

Processing circuitry 2 a performs information processing and isaccessible to memory 3 a. For example, processing circuitry 2 a isexclusive or general electronic circuitry that encodes a video.Processing circuitry 2 a may be a processor such as a central processingunit (CPU). Processing circuitry 2 a may be an aggregate of a pluralityof electronic circuits. Moreover, for example, processing circuitry 2 amay perform the functions of two or more constituent elements among theplurality of constituent elements of encoder 100 illustrated in FIG. 1,except the constituent elements that store information.

Memory 3 a is an exclusive or general memory for storing informationused by processing circuitry 2 a to encode a video. Memory 3 a may be anelectronic circuit, may be connected to processing circuitry 2 a, or maybe included in processing circuitry 2 a. Memory 3 a may be an aggregateof a plurality of electronic circuits. Memory 3 a may be a magneticdisc, an optical disc, or the like, or may be expressed as storage, arecording medium, or the like. Memory 3 a may be a non-volatile memoryor a volatile memory.

For example, memory 3 a may store a video to be encoded, or may store abitstream corresponding to an encoded video. Memory 3 a may store aprogram for causing processing circuitry 2 a to encode a video.

Moreover, for example, memory 3 a may perform the functions of, amongthe plurality of constituent elements of encoder 100 illustrated in FIG.1, the constituent elements that store information. Specifically, memory3 a may perform the functions of block memory 118 and frame memory 122illustrated in FIG. 1. More specifically, memory 3 a may store aprocessed sub-block, a processed block, a processed picture, etc.

It should be noted that not all of the plurality of constituent elementsillustrated in FIG. 1 need to be implemented by encoder 100, and not allof the processes described above need to be performed by encoder 100.Some of the constituent elements illustrated in FIG. 1 may be includedin another device, and some of the processes described above may beperformed by another device.

FIG. 15B is a flow chart illustrating operations performed by encoder 1a including processing circuitry 2 a and memory 3 a.

Using memory 3 a, processing circuitry 2 a first generates a luminancefinal prediction image and a chrominance final prediction image byperforming inter frame prediction on a current block (step S10 a). Next,processing circuitry 2 a encodes the current block using the luminancefinal prediction image and the chrominance final prediction image (stepS20 a). Here, in the inter frame prediction of step S10 a, processingcircuitry 2 a obtains two prediction images from two reference picturesby performing motion compensation using two motion vectors of thecurrent block (step S11 a). Next, processing circuitry 2 a derives aluminance gradient value of each pixel position in each of the twoprediction images by referring to a pixel surrounding the pixel positionin each of the two reference pictures (step S12 a). Then, processingcircuitry 2 a derives a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block (step S13 a). After that, processingcircuitry 2 a generates the luminance final prediction image using theluminance value and the luminance gradient value of the pixel positionin each of the two prediction images, and the luminance local motionestimation value of the pixel position in the current block (step S14a). Finally, processing circuitry 2 a generates the chrominance finalprediction image using at least one of the luminance gradient value ofthe pixel position in each of the two prediction images or the luminancelocal motion estimation value of the pixel position in the currentblock, and chrominance of the pixel position in each of the twoprediction images (step S15 a).

With this, the derivation of at least one of the chrominance gradientvalue of each pixel position in each of the two prediction images or thechrominance local motion estimation value of each pixel position in thecurrent block based on the chrominance can be omitted from thegeneration of the chrominance final prediction image. As a result, thereis a possibility of reducing the processing load of encoder 1 a andsimplifying the configuration of encoder 1 a.

FIG. 15C is a block diagram illustrating an implementation example of adecoder in Embodiment 2. Decoder 1 b includes processing circuitry 2 band memory 3 b. For example, the plurality of constituent elements ofdecoder 200 illustrated in FIG. 10 are implemented by processingcircuitry 2 b and memory 3 b illustrated in FIG. 15C.

Processing circuitry 2 b performs information processing and isaccessible to memory 3 b. For example, processing circuitry 2 b isexclusive or general electronic circuitry that decodes a video.Processing circuitry 2 b may be a processor such as a central processingunit (CPU). Processing circuitry 2 b may be an aggregate of a pluralityof electronic circuits. Moreover, for example, processing circuitry 2 bmay perform the functions of two or more constituent elements among theplurality of constituent elements of decoder 200 illustrated in FIG. 10,except the constituent elements that store information.

Memory 3 b is an exclusive or general memory for storing informationused by processing circuitry 2 b to decode a video. Memory 3 b may be anelectronic circuit, may be connected to processing circuitry 2 b, or maybe included in processing circuitry 2 b. Memory 3 b may be an aggregateof a plurality of electronic circuits. Memory 3 b may be a magneticdisc, an optical disc, or the like, or may be expressed as storage, arecording medium, or the like. Memory 3 b may be a non-volatile memoryor a volatile memory.

For example, memory 3 b may store a bitstream corresponding to anencoded video, or may store a video corresponding to a decodedbitstream. Memory 3 b may store a program for causing processingcircuitry 2 b to decode a video.

Moreover, for example, memory 2 b may perform the functions of, amongthe plurality of constituent elements of decoder 200 illustrated in FIG.10, the constituent elements that store information. Specifically,memory 3 b may perform the functions of block memory 210 and framememory 214 illustrated in FIG. 10. More specifically, memory 3 b maystore a processed sub-block, a processed block, a processed picture,etc.

It should be noted that not all of the plurality of constituent elementsillustrated in FIG. 10 need to be implemented by decoder 200, and notall of the processes described above need to be performed by decoder200. Some of the constituent elements illustrated in FIG. 10 may beincluded in another device, and some of the processes described abovemay be performed by another device.

FIG. 15D is a flow chart operations performed by decoder 1 b includingprocessing circuitry 2 b and memory 3 b.

Using memory 3 b, processing circuitry 2 b first generates a luminancefinal prediction image and a chrominance final prediction image byperforming inter frame prediction on a current block (step Slob). Next,processing circuitry 2 b decodes the current block using the luminancefinal prediction image and the chrominance final prediction image (stepS20 b). Here, in the inter frame prediction of step S10 b, processingcircuitry 2 b obtains two prediction images from two reference picturesby performing motion compensation using two motion vectors of thecurrent block (step S11 b). Next, processing circuitry 2 b derives aluminance gradient value of each pixel position in each of the twoprediction images by referring to a pixel surrounding the pixel positionin each of the two reference pictures (step S12 b). Then, processingcircuitry 2 b derives a luminance local motion estimation value for eachpixel position in the current block using a luminance value and theluminance gradient value in each of the two prediction images, theluminance value and the luminance gradient value corresponding to thepixel position in the current block (step S13 b). After that, processingcircuitry 2 b generates the luminance final prediction image using theluminance value and the luminance gradient value of the pixel positionin each of the two prediction images, and the luminance local motionestimation value of the pixel position in the current block (step S14b). Finally, processing circuitry 2 b generates the chrominance finalprediction image using at least one of the luminance gradient value ofthe pixel position in each of the two prediction images or the luminancelocal motion estimation value of the pixel position in the currentblock, and chrominance of the pixel position in each of the twoprediction images(step S15 b).

With this, decoder 1 b produces the same advantageous effect as encoderla. In other words, the derivation of at least one of the chrominancegradient value of each pixel position in each of the two predictionimages or the chrominance local motion estimation value of each pixelposition in the current block based on the chrominance can be omittedfrom the generation of the chrominance final prediction image. As aresult, there is a possibility of reducing the processing load ofdecoder 1 b and simplifying the configuration of decoder 1 b.

[Supplemental Information]

The encoder and the decoder in each of the aforementioned embodimentsmay be used respectively as an image encoder and an image decoder, ormay be used respectively as a video encoder and a video decoder.

In the aforementioned embodiments, each of the constituent elements maybe configured in the form of an exclusive hardware product, or may beimplemented by executing a software program suitable for the constituentelement. Each of the constituent elements may be implemented by means ofa program execution unit, such as a CPU or a processor, reading andexecuting a software program recorded on a recording medium such as ahard disk or a semiconductor memory.

Specifically, the encoder and the decoder may each include processingcircuitry and storage electrically connected to the processing circuitryand accessible from the processing circuitry.

The processing circuitry includes at least one of an exclusive hardwareproduct or a program execution unit, and performs processing using thestorage. When the processing circuitry includes a program executionunit, the storage stores a software program executed by the programexecution unit.

Here, the software for implementing, for example, the encoder, thedecoder, etc. in each of the aforementioned embodiments includes aprogram as indicated below.

Specifically, the program may cause a computer to execute the processingin accordance with the flow chart illustrated in any of FIG. 5B, FIG.5D, FIG. 12 to FIG. 14, FIG. 15B, and FIG. 15D.

The constituent elements may be circuits as described above. Thecircuits may constitute circuitry as a whole, or may be individualcircuits. Each constituent element may be implemented by a generalprocessor, or may be implemented by an exclusive processor.

Moreover, processing executed by a particular constituent element may beexecuted by another constituent element. The processing execution ordermay be modified, or a plurality of processes may be executed inparallel. Further, an encoding and decoding device may include theencoder and the decoder.

The ordinal numbers such as “first” and “second” used in the descriptionmay be changed as appropriate. A new ordinal number may be given to theconstituent elements, or the ordinal numbers of the constituent elementsmay be removed.

Although some aspects of the encoder and the decoder have been describedabove based on each embodiment, the aspects of the encoder and thedecoder are not limited to the embodiment. Various modifications to theembodiments that are conceivable to those skilled in the art, as well asembodiments resulting from combinations of constituent elements indifferent embodiments, may be included within the scope of the aspectsof the encoder and the decoder, so long as they do not depart from theessence of the present disclosure.

[Combination with Other Aspects]

The present aspect may be implemented in combination with one or more ofthe other aspects in the present disclosure. In addition, part of theprocesses in the flow charts, part of the constituent elements of thedevices, and part of the syntax described in the present aspect may beimplemented in combination with the other aspects.

Embodiment 3

As described in each of the above embodiments, each functional block cantypically be realized as an MPU and memory, for example. Moreover,processes performed by each of the functional blocks are typicallyrealized by a program execution unit, such as a processor, reading andexecuting software (a program) recorded on a recording medium such asROM. The software may be distributed via, for example, downloading, andmay be recorded on a recording medium such as semiconductor memory anddistributed. Note that each functional block can, of course, also berealized as hardware (dedicated circuit).

Moreover, the processing described in each of the embodiments may berealized via integrated processing using a single apparatus (system),and, alternatively, may be realized via decentralized processing using aplurality of apparatuses. Moreover, the processor that executes theabove-described program may be a single processor or a plurality ofprocessors. In other words, integrated processing may be performed, and,alternatively, decentralized processing may be performed.

Embodiments of the present disclosure are not limited to the aboveexemplary embodiments; various modifications may be made to theexemplary embodiments, the results of which are also included within thescope of the embodiments of the present disclosure.

Next, application examples of the moving picture encoding method (imageencoding method) and the moving picture decoding method (image decodingmethod) described in each of the above embodiments and a system thatemploys the same will be described. The system is characterized asincluding an image encoder that employs the image encoding method, animage decoder that employs the image decoding method, and an imageencoder/decoder that includes both the image encoder and the imagedecoder. Other configurations included in the system may be modified ona case-by-case basis.

USAGE EXAMPLES

FIG. 16 illustrates an overall configuration of content providing systemex100 for implementing a content distribution service. The area in whichthe communication service is provided is divided into cells of desiredsizes, and base stations ex106, ex107, ex108, ex109, and ex110, whichare fixed wireless stations, are located in respective cells. In contentproviding system ex100, devices including computer ex111, gaming deviceex112, camera ex113, home appliance ex114, and smartphone ex115 areconnected to internet ex101 via internet service provider ex102 orcommunications network ex104 and base stations ex106 through ex110.Content providing system ex100 may combine and connect any combinationof the above elements. The devices may be directly or indirectlyconnected together via a telephone network or near field communicationrather than via base stations ex106 through ex110, which are fixedwireless stations.

Moreover, streaming server ex103 is connected to devices includingcomputer ex111, gaming device ex112, camera ex113, home appliance ex114,and smartphone ex115 via, for example, internet ex101. Streaming serverex103 is also connected to, for example, a terminal in a hotspot inairplane ex117 via satellite ex116.

Note that instead of base stations ex106 through ex110, wireless accesspoints or hotspots may be used. Streaming server ex103 may be connectedto communications network ex104 directly instead of via internet ex101or internet service provider ex102, and may be connected to airplaneex117 directly instead of via satellite ex116.

Camera ex113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex115 is a smartphone device,cellular phone, or personal handyphone system (PHS) phone that canoperate under the mobile communications system standards of the typical2G, 3G, 3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex118 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex103 via, for example, base stationex106. When live streaming, a terminal (e.g., computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, orairplane ex117) performs the encoding processing described in the aboveembodiments on still-image or video content captured by a user via theterminal, multiplexes video data obtained via the encoding and audiodata obtained by encoding audio corresponding to the video, andtransmits the obtained data to streaming server ex103. In other words,the terminal functions as the image encoder according to one aspect ofthe present disclosure.

Streaming server ex103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, andterminals inside airplane ex117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed datadecode and reproduce the received data. In other words, the devices eachfunction as the image decoder according to one aspect of the presentdisclosure.

[Decentralized Processing]

Streaming server ex103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client is dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some kind ofan error or a change in connectivity due to, for example, a spike intraffic, it is possible to stream data stably at high speeds since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers or switchingthe streaming duties to a different edge server, and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex113 or the like extracts a feature amountfrom an image, compresses data related to the feature amount asmetadata, and transmits the compressed metadata to a server. Forexample, the server determines the significance of an object based onthe feature amount and changes the quantization accuracy accordingly toperform compression suitable for the meaning of the image. Featureamount data is particularly effective in improving the precision andefficiency of motion vector prediction during the second compressionpass performed by the server. Moreover, encoding that has a relativelylow processing load, such as variable length coding (VLC), may behandled by the terminal, and encoding that has a relatively highprocessing load, such as context-adaptive binary arithmetic coding(CABAC), may be handled by the server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real-time.

Moreover, since the videos are of approximately the same scene,management and/or instruction may be carried out by the server so thatthe videos captured by the terminals can be cross-referenced. Moreover,the server may receive encoded data from the terminals, change referencerelationship between items of data or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Moreover, the server may stream video data after performing transcodingto convert the encoding format of the video data. For example, theserver may convert the encoding format from MPEG to VP, and may convertH.264 to H.265.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

[3D, Multi-Angle]

In recent years, usage of images or videos combined from images orvideos of different scenes concurrently captured or the same scenecaptured from different angles by a plurality of terminals such ascamera ex113 and/or smartphone ex115 has increased. Videos captured bythe terminals are combined based on, for example, theseparately-obtained relative positional relationship between theterminals, or regions in a video having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. Note that the server may separatelyencode three-dimensional data generated from, for example, a pointcloud, and may, based on a result of recognizing or tracking a person orobject using three-dimensional data, select or reconstruct and generatea video to be transmitted to a reception terminal from videos capturedby a plurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting, from three-dimensional datareconstructed from a plurality of images or videos, a video from aselected viewpoint. Furthermore, similar to with video, sound may berecorded from relatively different angles, and the server may multiplex,with the video, audio from a specific angle or space in accordance withthe video, and transmit the result.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyesand perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server superimposes virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoder may obtain orstore virtual object information and three-dimensional data, generatetwo-dimensional images based on movement from the perspective of theuser, and then generate superimposed data by seamlessly connecting theimages. Alternatively, the decoder may transmit, to the server, motionfrom the perspective of the user in addition to a request for virtualobject information, and the server may generate superimposed data basedon three-dimensional data stored in the server in accordance with thereceived motion, and encode and stream the generated superimposed datato the decoder. Note that superimposed data includes, in addition to RGBvalues, an a value indicating transparency, and the server sets the avalue for sections other than the object generated fromthree-dimensional data to, for example, 0, and may perform the encodingwhile those sections are transparent. Alternatively, the server may setthe background to a predetermined RGB value, such as a chroma key, andgenerate data in which areas other than the object are set as thebackground.

Decoding of similarly streamed data may be performed by the client(i.e., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV. This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area or inspect a region in further detail upclose.

In the future, both indoors and outdoors, in situations in which aplurality of wireless connections are possible over near, mid, and fardistances, it is expected to be able to seamlessly receive content evenwhen switching to data appropriate for the current connection, using astreaming system standard such as MPEG-DASH. With this, the user canswitch between data in real time while freely selecting a decoder ordisplay apparatus including not only his or her own terminal, but also,for example, displays disposed indoors or outdoors. Moreover, based on,for example, information on the position of the user, decoding can beperformed while switching which terminal handles decoding and whichterminal handles the displaying of content. This makes it possible to,while in route to a destination, display, on the wall of a nearbybuilding in which a device capable of displaying content is embedded oron part of the ground, map information while on the move. Moreover, itis also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal or when encoded data is copied to an edge server in a contentdelivery service.

[Scalable Encoding]

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 17, that is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 17. Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode up to based oninternal factors, such as the processing ability on the decoder side,and external factors, such as communication bandwidth, the decoder sidecan freely switch between low resolution content and high resolutioncontent while decoding. For example, in a case in which the user wantsto continue watching, at home on a device such as a TV connected to theinternet, a video that he or she had been previously watching onsmartphone ex115 while on the move, the device can simply decode thesame stream up to a different layer, which reduces server side load.

Furthermore, in addition to the configuration described above in whichscalability is achieved as a result of the pictures being encoded perlayer and the enhancement layer is above the base layer, the enhancementlayer may include metadata based on, for example, statisticalinformation on the image, and the decoder side may generate high imagequality content by performing super-resolution imaging on a picture inthe base layer based on the metadata. Super-resolution imaging may beimproving the SN ratio while maintaining resolution and/or increasingresolution. Metadata includes information for identifying a linear or anon-linear filter coefficient used in super-resolution processing, orinformation identifying a parameter value in filter processing, machinelearning, or least squares method used in super-resolution processing.

Alternatively, a configuration in which a picture is divided into, forexample, tiles in accordance with the meaning of, for example, an objectin the image, and on the decoder side, only a partial region is decodedby selecting a tile to decode, is also acceptable. Moreover, by storingan attribute about the object (person, car, ball, etc.) and a positionof the object in the video (coordinates in identical images) asmetadata, the decoder side can identify the position of a desired objectbased on the metadata and determine which tile or tiles include thatobject. For example, as illustrated in FIG. 18, metadata is stored usinga data storage structure different from pixel data such as an SEImessage in HEVC. This metadata indicates, for example, the position,size, or color of the main object.

Moreover, metadata may be stored in units of a plurality of pictures,such as stream, sequence, or random access units. With this, the decoderside can obtain, for example, the time at which a specific personappears in the video, and by fitting that with picture unit information,can identify a picture in which the object is present and the positionof the object in the picture.

[Web Page Optimization]

FIG. 19 illustrates an example of a display screen of a web page on, forexample, computer ex111. FIG. 20 illustrates an example of a displayscreen of a web page on, for example, smartphone ex115. As illustratedin FIG. 19 and FIG. 20, a web page may include a plurality of imagelinks which are links to image content, and the appearance of the webpage differs depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoder) displays, as the image links,still images included in the content or I pictures, displays video suchas an animated gif using a plurality of still images or I pictures, forexample, or receives only the base layer and decodes and displays thevideo.

When an image link is selected by the user, the display apparatusdecodes giving the highest priority to the base layer. Note that ifthere is information in the HTML code of the web page indicating thatthe content is scalable, the display apparatus may decode up to theenhancement layer. Moreover, in order to guarantee real timereproduction, before a selection is made or when the bandwidth isseverely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Moreover, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

[Autonomous Driving]

When transmitting and receiving still image or video data such two- orthree-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., includingthe reception terminal is mobile, the reception terminal can seamlesslyreceive and decode while switching between base stations among basestations ex106 through ex110 by transmitting information indicating theposition of the reception terminal upon reception request. Moreover, inaccordance with the selection made by the user, the situation of theuser, or the bandwidth of the connection, the reception terminal candynamically select to what extent the metadata is received or to whatextent the map information, for example, is updated.

With this, in content providing system ex100, the client can receive,decode, and reproduce, in real time, encoded information transmitted bythe user.

[Streaming of Individual Content]

In content providing system ex100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, short content from anindividual is also possible. Moreover, such content from individuals islikely to further increase in popularity. The server may first performediting processing on the content before the encoding processing inorder to refine the individual content. This may be achieved with, forexample, the following configuration.

In real-time while capturing video or image content or after the contenthas been captured and accumulated, the server performs recognitionprocessing based on the raw or encoded data, such as capture errorprocessing, scene search processing, meaning analysis, and/or objectdetection processing. Then, based on the result of the recognitionprocessing, the server—either when prompted or automatically—edits thecontent, examples of which include: correction such as focus and/ormotion blur correction; removing low-priority scenes such as scenes thatare low in brightness compared to other pictures or out of focus; objectedge adjustment; and color tone adjustment. The server encodes theedited data based on the result of the editing. It is known thatexcessively long videos tend to receive fewer views. Accordingly, inorder to keep the content within a specific length that scales with thelength of the original video, the server may, in addition to thelow-priority scenes described above, automatically clip out scenes withlow movement based on an image processing result. Alternatively, theserver may generate and encode a video digest based on a result of ananalysis of the meaning of a scene.

Note that there are instances in which individual content may includecontent that infringes a copyright, moral right, portrait rights, etc.Such an instance may lead to an unfavorable situation for the creator,such as when content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Moreover, the server may be configuredto recognize the faces of people other than a registered person inimages to be encoded, and when such faces appear in an image, forexample, apply a mosaic filter to the face of the person. Alternatively,as pre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background be processed, and the server may process the specifiedregion by, for example, replacing the region with a different image orblurring the region. If the region includes a person, the person may betracked in the moving picture, and the head region may be replaced withanother image as the person moves.

Moreover, since there is a demand for real-time viewing of contentproduced by individuals, which tends to be small in data size, thedecoder first receives the base layer as the highest priority andperforms decoding and reproduction, although this may differ dependingon bandwidth. When the content is reproduced two or more times, such aswhen the decoder receives the enhancement layer during decoding andreproduction of the base layer and loops the reproduction, the decodermay reproduce a high image quality video including the enhancementlayer. If the stream is encoded using such scalable encoding, the videomay be low quality when in an unselected state or at the start of thevideo, but it can offer an experience in which the image quality of thestream progressively increases in an intelligent manner. This is notlimited to just scalable encoding; the same experience can be offered byconfiguring a single stream from a low quality stream reproduced for thefirst time and a second stream encoded using the first stream as areference.

Other Usage Examples

The encoding and decoding may be performed by LSI ex500, which istypically included in each terminal. LSI ex500 may be configured of asingle chip or a plurality of chips. Software for encoding and decodingmoving pictures may be integrated into some type of a recording medium(such as a CD-ROM, a flexible disk, or a hard disk) that is readable by,for example, computer ex111, and the encoding and decoding may beperformed using the software. Furthermore, when smartphone ex115 isequipped with a camera, the video data obtained by the camera may betransmitted. In this case, the video data is coded by LSI ex500 includedin smartphone ex115.

Note that LSI ex500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content or when the terminalis not capable of executing a specific service, the terminal firstdownloads a codec or application software then obtains and reproducesthe content.

Aside from the example of content providing system ex100 that usesinternet ex101, at least the moving picture encoder (image encoder) orthe moving picture decoder (image decoder) described in the aboveembodiments may be implemented in a digital broadcasting system. Thesame encoding processing and decoding processing may be applied totransmit and receive broadcast radio waves superimposed with multiplexedaudio and video data using, for example, a satellite, even though thisis geared toward multicast whereas unicast is easier with contentproviding system ex100.

[Hardware Configuration]

FIG. 21 illustrates smartphone ex115. FIG. 22 illustrates aconfiguration example of smartphone ex115. Smartphone ex115 includesantenna ex450 for transmitting and receiving radio waves to and frombase station ex110, camera ex465 capable of capturing video and stillimages, and display ex458 that displays decoded data, such as videocaptured by camera ex465 and video received by antenna ex450. Smartphoneex115 further includes user interface ex466 such as a touch panel, audiooutput unit ex457 such as a speaker for outputting speech or otheraudio, audio input unit ex456 such as a microphone for audio input,memory ex467 capable of storing decoded data such as captured video orstill images, recorded audio, received video or still images, and mail,as well as decoded data, and slot ex464 which is an interface for SIMex468 for authorizing access to a network and various data. Note thatexternal memory may be used instead of memory ex467.

Moreover, main controller ex460 which comprehensively controls displayex458 and user interface ex466, power supply circuit ex461, userinterface input controller ex462, video signal processor ex455, camerainterface ex463, display controller ex459, modulator/demodulator ex452,multiplexer/demultiplexer ex453, audio signal processor ex454, slotex464, and memory ex467 are connected via bus ex470.

When the user turns the power button of power supply circuit ex461 on,smartphone ex115 is powered on into an operable state by each componentbeing supplied with power from a battery pack.

Smartphone ex115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex460, whichincludes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex456 is converted into a digital audiosignal by audio signal processor ex454, and this is applied with spreadspectrum processing by modulator/demodulator ex452 and digital-analogconversion and frequency conversion processing by transmitter/receiverex451, and then transmitted via antenna ex450. The received data isamplified, frequency converted, and analog-digital converted, inversespread spectrum processed by modulator/demodulator ex452, converted intoan analog audio signal by audio signal processor ex454, and then outputfrom audio output unit ex457. In data transmission mode, text,still-image, or video data is transmitted by main controller ex460 viauser interface input controller ex462 as a result of operation of, forexample, user interface ex466 of the main body, and similar transmissionand reception processing is performed. In data transmission mode, whensending a video, still image, or video and audio, video signal processorex455 compression encodes, via the moving picture encoding methoddescribed in the above embodiments, a video signal stored in memoryex467 or a video signal input from camera ex465, and transmits theencoded video data to multiplexer/demultiplexer ex453. Moreover, audiosignal processor ex454 encodes an audio signal recorded by audio inputunit ex456 while camera ex465 is capturing, for example, a video orstill image, and transmits the encoded audio data tomultiplexer/demultiplexer ex453. Multiplexer/demultiplexer ex453multiplexes the encoded video data and encoded audio data using apredetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex452 andtransmitter/receiver ex451, and transmits the result via antenna ex450.

When video appended in an email or a chat, or a video linked from a webpage, for example, is received, in order to decode the multiplexed datareceived via antenna ex450, multiplexer/demultiplexer ex453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex455 via synchronous busex470, and supplies the encoded audio data to audio signal processorex454 via synchronous bus ex470. Video signal processor ex455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex458 via display controller ex459. Moreover, audiosignal processor ex454 decodes the audio signal and outputs audio fromaudio output unit ex457. Note that since real-time streaming is becomingmore and more popular, there are instances in which reproduction of theaudio may be socially inappropriate depending on the user's environment.Accordingly, as an initial value, a configuration in which only videodata is reproduced, i.e., the audio signal is not reproduced, ispreferable. Audio may be synchronized and reproduced only when an input,such as when the user clicks video data, is received.

Although smartphone ex115 was used in the above example, threeimplementations are conceivable: a transceiver terminal including bothan encoder and a decoder; a transmitter terminal including only anencoder; and a receiver terminal including only a decoder. Further, inthe description of the digital broadcasting system, an example is givenin which multiplexed data obtained as a result of video data beingmultiplexed with, for example, audio data, is received or transmitted,but the multiplexed data may be video data multiplexed with data otherthan audio data, such as text data related to the video. Moreover, thevideo data itself rather than multiplexed data maybe received ortransmitted.

Although main controller ex460 including a CPU is described ascontrolling the encoding or decoding processes, terminals often includeGPUs. Accordingly, a configuration is acceptable in which a large areais processed at once by making use of the performance ability of the GPUvia memory shared by the CPU and GPU or memory including an address thatis managed so as to allow common usage by the CPU and GPU. This makes itpossible to shorten encoding time, maintain the real-time nature of thestream, and reduce delay. In particular, processing relating to motionestimation, deblocking filtering, sample adaptive offset (SAO), andtransformation/quantization can be effectively carried out by the GPUinstead of the CPU in units of, for example pictures, all at once.

Although only some exemplary embodiments of the present disclosure havebeen described in detail above, those skilled in the art will readilyappreciate that many modifications are possible in the exemplaryembodiments without materially departing from the novel teachings andadvantages of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. cl INDUSTRIAL APPLICABILITY

The encoder and the decoder according to the present disclosure producean advantageous effect of raising the possibility of furtherimprovement, are applicable to, for example, television receivers,digital video recorders, car navigation systems, mobile phones, digitalcameras, digital video cameras, teleconferencing systems, electronicmirrors, etc, and have a high utility value.

1-12. (canceled)
 13. An encoding method comprising: in a firstbi-directional optical flow (BIO) process on first luma predictionimages to generate a second luma prediction image: calculating lumagradient values of respective pixel positions of each of the first lumaprediction images; and calculating luma local motion estimation valuesbased on the luma gradient values; and in a second BIO process on firstchroma prediction images to generate a second chroma prediction image:performing at least one of (i) deriving chroma gradient values based onthe luma gradient values or (ii) deriving chroma local motion estimationvalues based on the luma local motion estimation values.
 14. A decodingmethod comprising: in a first bi-directional optical flow (BIO) processon first luma prediction images to generate a second luma predictionimage: calculating luma gradient values of respective pixel positions ofeach of the first luma prediction images; and calculating luma localmotion estimation values based on the luma gradient values; and in asecond BIO process on first chroma prediction images to generate asecond chroma prediction image: performing at least one of (i) derivingchroma gradient values based on the luma gradient values or (ii)deriving chroma local motion estimation values based on the luma localmotion estimation values.